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Research Engineer, Knowledge Graph Intelligence
at Point72
Mid LevelNo visa sponsorshipPython
Posted 21 hours ago
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- Compensation
- $175,000 – $275,000 USD
- City
- Country
- United States
Currency: $ (USD)
**Research Engineer, Knowledge Graph Intelligence**, drives AI-driven graph insights. Develops graphs, models data relationships, optimizes search & recommendation systems. Required: 5+ years' graph data experience, proficient in Neo4j, spark, machine learning algorithms, and Python. Experience with knowledge graphs and/or graph neural networks is a plus. M.S. or Ph.D. in Computer Science, Mathematics, or related field.
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Research Engineer, Knowledge Graph Intelligence Career
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","title":"Research Engineer, Knowledge Graph Intelligence","@type":"JobPosting","@context":"http://schema.org/"} CSJobDetailModule.init('{\"lastModifiedDateFormatted\":\"2026-06-25\",\"job\":{\"attributes\":{\"type\":\"Job__c\",\"url\":\"/services/data/v67.0/sobjects/Job__c/a03Vo00001mBpXjIAK\"},\"Id\":\"a03Vo00001mBpXjIAK\",\"Name\":\"Research Engineer, Knowledge Graph Intelligence\",\"Assigned_Internal_Recruiter__c\":\"005Vo00000XyPLsIAN\",\"Job_Code__c\":\"IVS-0015003\",\"Experience__c\":\"Experienced Professionals\",\"Company__c\":\"001j000000VbgAOAAZ\",\"Posted_Location__c\":\"New York\",\"Area__c\":\"Legal & Compliance;Technology & Engineering\",\"Team__c\":\"Compliance\",\"Job_Description_External__c\":\"\u003Ch3\u003EA Career with Point72’s Surveillance Team\u003C/h3\u003E\\n\u003Cp\u003EPoint72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations. \u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003EWhat you’ll do\u003C/h3\u003E\\n\u003Cp\u003EAs a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. 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When you work here, we provide:\u003C/p\u003E\\n\u003Cul\u003E\u003Cli\u003EFully-paid health care benefits\u003C/li\u003E\u003Cli\u003EGenerous parental and family leave policies\u003C/li\u003E\u003Cli\u003EMental and physical wellness programs\u003C/li\u003E\u003Cli\u003EVolunteer opportunities\u003C/li\u003E\u003Cli\u003ENon-profit matching gift program\u003C/li\u003E\u003Cli\u003ESupport for employee-led affinity groups representing women, minorities and the LGBT+ community\u003C/li\u003E\u003Cli\u003ETuition assistance\u003C/li\u003E\u003Cli\u003EA 401(k) savings program with an employer match and more\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EAbout Point72\u003C/h3\u003E\\n\u003Cp\u003EPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit \u003Ca href=\\\"https://www.Point72.com/working-here\\\\\\\" target=\\\"_blank\\\"\u003Ewww.Point72.com/working-here\u003C/a\u003E\u003C/p\u003E\u003Cbr\u003E\u003Cp\u003EThe annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. 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color: #18181a !important; } .c-menu-mega-careers ul a:focus, .c-menu-mega-careers ul a:hover { color: #b08725 !important; color: var(--p72-color-content-stronger) !important; } li.c-menu-mobile__menu-item > a.c-menu-mobile__link, li.c-menu-mobile__menu-item > a.c-menu-mobile__link span { color: #18181a !important; } li.c-menu-mobile__menu-item > a.c-menu-mobile__link:hover, li.c-menu-mobile__menu-item > a.c-menu-mobile__link:hover span { color: var(--p72-color-content-stronger, #b08725) !important; } li.c-menu-mobile__menu-item > a.c-menu-mobile__link, li.c-menu-mobile__menu-item > a.c-menu-mobile__link span { color: #18181a !important; } li.o-icon > a.o-icon:hover, li.o-icon > a.o-icon:hover span { color: var(--p72-color-content-stronger, #b08725) !important; } .o-button--outlined { background-color: transparent; color: black; border: 1px solid black; transition: all 0.3s ease; } .o-button--outlined:focus, .o-button--outlined:hover { background-color: var(--p72-color-button-background, #b08725); border-color: var(--p72-color-button-background, #b08725); color: var(--p72-color-button-text, #f5f4ee); } .c-menu-mega { opacity: 0; visibility: hidden; transform: translateY(5px); transition: opacity 0.15s ease-out, transform 0.15s ease-out; will-change: opacity, transform; } body.header-scrolled .c-header { top: var(--p72-cookie-consent-height, 0px) !important; } body.header-scrolled .c-menu-mobile { /*top: 0 !important;*/ } /* Header common style */ .c-header, .c-header.l-wrap, .c-header .l-wrap { transition: none !important; will-change: auto; } /* Optional: reset header when scrolled */ body.header-scrolled .c-header, body.header-scrolled .c-header.l-wrap, body.header-scrolled .c-header .l-wrap { top: 0 !important; } @media only screen and (max-width:768px) { .c-cookie-consent__container { padding: 8px 10px !important; } body.header-scrolled .c-header, body.header-scrolled .c-header.l-wrap { padding-top: 13px; !important; } body.header-scrolled .c-header .l-wrap { padding-top: 13px; !important; } .c-cookie-consent__content p,.c-cookie-consent__content a { max-width: 100% !important; font-family:"Aptos", sans-serif; font-size:14px !important; line-height:18.2px !important; } } /* ========================================================= Combined CSS: c-menu-mobile + u-hide-after--md + u-spacing--lg Includes required variables + hamburger related CSS ========================================================= */ /* ========================================================= Required Variables ========================================================= */ :root { --p72-header-height: 100px; --p72-space-xxs: 0.25rem; --p72-space-xs: 0.5rem; --p72-space-sm: 0.75rem; --p72-space: 1rem; --p72-space-md: 1.5rem; --p72-space-lg: 2rem; --p72-animation-duration: 0.4s; --p72-animation-duration-long: 0.6s; --p72-animation-timing: cubic-bezier(0.65, 0, 0.35, 1); --p72-z-index-5: 5; --p72-border-width: 1px; --p72-font-family-secondary: Aptos, sans-serif; --p72-font-weight-bold: 700; --p72-font-size-heading-xs: 1.25rem; --p72-line-height-tight: 1.1; --p72-letter-spacing-wide: 0.06em; --p72-typography-heading-xs: var(--p72-font-weight-bold) var(--p72-font-size-heading-xs) / var(--p72-line-height-tight) var(--p72-font-family-secondary); --p72-color-brand-cream: #f5f4ee; --p72-color-brand-gold: #b08725; --p72-color-brand-slate: #505a6b; --p72-color-brand-charcoal: #18181a; --p72-color-background: var(--p72-color-brand-charcoal); --p72-color-content: var(--p72-color-brand-cream); --p72-color-content-stronger: var(--p72-color-brand-gold); --p72-color-border: var(--p72-color-brand-slate); --p72-cookie-consent-height: 0px; --p72-icon-size-sm: 0.9375rem; } /* ========================================================= Utility: u-hide-after--md Hidden after medium breakpoint ========================================================= */ @media (min-width: 769px) { .u-hide-after--md { display: none !important; } } /* ========================================================= Utility: u-spacing--lg Adds large vertical spacing between direct children ========================================================= */ .u-spacing--lg > * + * { margin-top: 2rem; margin-top: var(--p72-space-lg); } /* ========================================================= Mobile Menu Container ========================================================= */ .c-menu-mobile { bottom: 0; height: calc(100% - var(--p72-cookie-consent-height)); overflow-y: scroll; padding: calc(100px + 1.5rem) 1.5rem 1.5rem; padding: calc(var(--p72-header-height) + var(--p72-space-md)) var(--p72-space-md) var(--p72-space-md) var(--p72-space-md); position: fixed; right: 0; top: var(--p72-cookie-consent-height) !important; transform: translate3d(100%, 0, 0); transition: all 0.6s cubic-bezier(0.65, 0, 0.35, 1); transition: all var(--p72-animation-duration-long) var(--p72-animation-timing); visibility: hidden; width: 100%; z-index: 5; z-index: var(--p72-z-index-5); background-color: var(--p72-color-background); color: var(--p72-color-content); } /* ========================================================= Mobile Menu Open State Add class c-menu-mobile-is-active to body or parent ========================================================= */ @media (max-width: 767px) { .c-menu-mobile-is-active .c-menu-mobile { transform: translateZ(0); visibility: visible; } body.c-menu-mobile-is-active { overflow: hidden; } } /* ========================================================= Mobile Menu Item ========================================================= */ .c-menu-mobile__menu-item { border-bottom: 1px solid #505a6b; border-bottom: var(--p72-border-width) solid var(--p72-color-border); display: flex; flex-flow: column nowrap; gap: 0.25rem; gap: var(--p72-space-xxs); overflow: hidden; width: 100%; } /* ========================================================= Mobile Menu Link / Button ========================================================= */ .c-menu-mobile__link { align-items: center; background: transparent; border: none; color: #f5f4ee; color: var(--p72-color-content); cursor: pointer; display: flex; font: 700 1.25rem/1.1 Aptos, sans-serif; font: var(--p72-typography-heading-xs); gap: 0.25rem; gap: var(--p72-space-xxs); justify-content: space-between; letter-spacing: 0.06em; letter-spacing: var(--p72-letter-spacing-wide); padding: 0.75rem 0; padding: var(--p72-space-sm) 0; text-transform: uppercase; transition: color 0.4s cubic-bezier(0.65, 0, 0.35, 1); transition: color var(--p72-animation-duration) var(--p72-animation-timing); width: 100%; text-align: left; } @media (max-width: 768px) { .c-menu-mobile__link { font-size: 1.0625rem; } } .c-menu-mobile__link:focus, .c-menu-mobile__link:hover { color: #b08725; color: var(--p72-color-content-stronger); } .c-menu-mobile__link svg { height: var(--p72-icon-size-sm); min-width: var(--p72-icon-size-sm); width: var(--p72-icon-size-sm); } /* ========================================================= Mobile Sub Menu ========================================================= */ .c-menu-mobile--sub-menu { display: none; } .c-menu-mobile--sub-menu ul { display: flex; flex-direction: column; gap: 0.25rem; gap: var(--p72-space-xxs); margin-bottom: 0.75rem; margin-bottom: var(--p72-space-sm); list-style: none; padding: 0; } .c-menu-mobile--sub-menu a { color: #f5f4ee; color: var(--p72-color-content); text-decoration: none; } @media (max-width: 768px) { .c-menu-mobile--sub-menu a { font-size: 0.875rem; } } .c-menu-mobile--sub-menu a:focus, .c-menu-mobile--sub-menu a:hover { color: #b08725; color: var(--p72-color-content-stronger); } /* Show submenu when menu item is active */ .c-menu-mobile__menu-item.this-is-active .c-menu-mobile--sub-menu { display: block; } /* ========================================================= Header Style When Mobile Menu Is Active ========================================================= */ .c-menu-mobile-is-active .c-header { backdrop-filter: blur(0); border-color: #505a6b; border-color: var(--p72-color-border); } /* ========================================================= Hamburger Button Base ========================================================= */ .o-button-hamburger { align-items: center; -webkit-appearance: none; -moz-appearance: none; appearance: none; background: transparent; border: none; color: #f5f4ee; color: var(--p72-color-content); cursor: pointer; display: flex; height: 50px; padding: 0; --p72-hamburger-line-height: 1px; --p72-hamburger-line-spacing: 6px; --p72-hamburger-line-width: 25px; --p72-hamburger-lines-total-height: calc( var(--p72-hamburger-line-spacing) * 2 + var(--p72-hamburger-line-height) * 3 ); } .o-button-hamburger__label { font: 700 1rem/1.1 Aptos, sans-serif; letter-spacing: 0.06em; letter-spacing: var(--p72-letter-spacing-wide); text-transform: uppercase; } .o-button-hamburger__lines { height: var(--p72-hamburger-lines-total-height); margin-left: 0.25rem; margin-left: var(--p72-space-xxs); position: relative; transition: transform 0.5s ease-in-out; width: var(--p72-hamburger-line-width); } .o-button-hamburger__line { background-color: currentcolor; height: var(--p72-hamburger-line-height); left: 0; position: absolute; transition: transform 0.3s ease, top 0.3s ease, opacity 0.3s ease; width: 100%; } .o-button-hamburger__line:first-child { top: 0; } .o-button-hamburger__line:nth-child(2) { top: calc( var(--p72-hamburger-line-spacing) + var(--p72-hamburger-line-height) ); } .o-button-hamburger__line:nth-child(3) { top: calc( (var(--p72-hamburger-line-spacing) + var(--p72-hamburger-line-height)) * 2 ); } /* ========================================================= Hamburger Active Animation Triggered by .c-menu-mobile-is-active ========================================================= */ .c-menu-mobile-is-active .o-button-hamburger__line:first-child { top: 50%; transform: rotate(45deg); } .c-menu-mobile-is-active .o-button-hamburger__line:nth-child(2) { opacity: 0; } .c-menu-mobile-is-active .o-button-hamburger__line:nth-child(3) { top: 50%; transform: rotate(-45deg); } /** * Extracted scroll-related functionality from the bundled app. * * Requires: * - GSAP * - ScrollTrigger * - Optional: jQuery if using the jQuery-based class add below * * If you are using ES modules: * * import gsap from "gsap"; * import ScrollTrigger from "gsap/ScrollTrigger"; * * gsap.registerPlugin(ScrollTrigger); */ /* ========================================================================== Cookie consent scroll/resize height tracking ========================================================================== */ const COOKIE_NOTICE_KEY = "p72_cookie_notice_dismissed"; const cookieConsentScroll = { _raf: null, _scrollBound: false, _onScroll: null, isDismissed() { try { return sessionStorage.getItem(COOKIE_NOTICE_KEY) === "1"; } catch (error) { return false; } }, setDismissed() { try { sessionStorage.setItem(COOKIE_NOTICE_KEY, "1"); } catch (error) {} }, showBanner() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { banner.classList.remove("is-hidden"); banner.classList.add("is-visible"); this.updateHeightVar(); this.bindScroll(); } }, hideBanner() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { banner.classList.remove("is-visible"); banner.classList.add("is-hidden"); this.unbindScroll(); this.updateHeightVar(); } }, updateHeightVar() { const banner = document.querySelector(".js-cookie-consent"); let height = 0; if (banner && !banner.classList.contains("is-hidden")) { const rect = banner.getBoundingClientRect(); height = Math.min( Math.max(rect.bottom, 0), banner.offsetHeight ); } document.documentElement.style.setProperty( "--p72-cookie-consent-height", `${height}px` ); }, onScroll() { if (!this._raf) { this._raf = window.requestAnimationFrame(() => { this._raf = null; this.updateHeightVar(); }); } }, bindScroll() { if (!this._scrollBound) { this._scrollBound = true; this._onScroll = this.onScroll.bind(this); window.addEventListener("scroll", this._onScroll, { passive: true, }); window.addEventListener("resize", this._onScroll, { passive: true, }); } }, unbindScroll() { if (this._scrollBound) { this._scrollBound = false; window.removeEventListener("scroll", this._onScroll); window.removeEventListener("resize", this._onScroll); } }, observeHeight() { const banner = document.querySelector(".js-cookie-consent"); if (!banner || typeof ResizeObserver === "undefined") return; new ResizeObserver(() => this.updateHeightVar()).observe(banner); }, handleClose() { this.setDismissed(); this.hideBanner(); }, init() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { if (this.isDismissed()) { this.updateHeightVar(); } else { this.showBanner(); } this.observeHeight(); } else { document.documentElement.style.setProperty( "--p72-cookie-consent-height", "0px" ); } }, }; /* ========================================================================== Smooth anchor scrolling with header offset ========================================================================== */ function getAnchorTarget(hash) { if (!hash || hash === "#") return null; const id = hash.startsWith("#") ? hash.substring(1) : hash; let target = document.getElementById(id); if (!target) { try { target = document.querySelector(hash); } catch (error) { return null; } } return target; } function scrollToElementWithHeaderOffset(element) { const headerHeight = parseInt( getComputedStyle(document.documentElement) .getPropertyValue("--p72-header-height") ) || 0; const top = element.getBoundingClientRect().top + window.pageYOffset - headerHeight; window.scrollTo({ top, behavior: "smooth", }); } function initSmoothAnchorScrolling() { document.addEventListener("click", function (event) { const link = event.target.closest( 'a[href^="#"]:not([href="#"])' ); if (!link) return; const href = link.getAttribute("href"); const target = getAnchorTarget(href); if (target) { event.preventDefault(); scrollToElementWithHeaderOffset(target); if (history.pushState) { history.pushState(null, null, href); } } }); if (window.location.hash) { setTimeout(() => { const target = getAnchorTarget(window.location.hash); if (target) { scrollToElementWithHeaderOffset(target); } }, 100); } } /* ========================================================================== GSAP ScrollTrigger animations ========================================================================== */ function initGsapScrollAnimations() { if (typeof gsap === "undefined" || typeof ScrollTrigger === "undefined") { console.warn("GSAP or ScrollTrigger is not available."); return; } gsap.registerPlugin(ScrollTrigger); document.querySelectorAll(".js-gsap-trigger").forEach((trigger) => { /** * Fade in on scroll */ const fadeItems = trigger.querySelectorAll(".js-gsap-fade-in"); if (fadeItems.length > 0) { fadeItems.forEach((item, index) => { gsap.to(item, { opacity: 1, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, }); }); } /** * Scale in on scroll */ const scaleItems = trigger.querySelectorAll(".js-gsap-scale-in"); if (scaleItems.length > 0) { scaleItems.forEach((item, index) => { gsap.to(item, { scale: 1, opacity: 1, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, transformOrigin: "center center", }); }); } /** * Slide up on scroll */ const slideUpItems = trigger.querySelectorAll(".js-gsap-slide-in-up"); if (slideUpItems.length > 0) { slideUpItems.forEach((item, index) => { gsap.to(item, { opacity: 1, y: 0, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, }); }); } /** * Card entrance animation * * Note: * In the original bundle this is inside `.js-gsap-trigger`, * but it is not actually tied to ScrollTrigger. It runs immediately. */ const cards = trigger.querySelectorAll(".js-card-animate"); if (cards.length > 0) { console.log("Found cards to animate:", cards.length); gsap.set(cards, { opacity: 0, y: 12, filter: "blur(0.5px)", clearProps: "none", }); gsap.to(cards, { opacity: 1, y: 0, filter: "blur(0px)", duration: 0.3, ease: "power2.out", stagger: 0.03, delay: 0.05, }); } }); /** * Generic scroll class trigger */ gsap.utils.toArray(".u-scroll-animation").forEach((element) => { ScrollTrigger.create({ trigger: element, start: "top 90%", onEnter: () => { element.classList.add("u-scroll-animate"); }, }); }); } /* ========================================================================== Load-more card animation ========================================================================== */ function initLoadMoreScrollRelatedAnimation() { if (typeof jQuery === "undefined") { console.warn("jQuery is not available."); return; } if (typeof gsap === "undefined") { console.warn("GSAP is not available."); return; } const $ = jQuery; $(".js-button-load-more").on("click", () => { const hiddenItems = $(".js-filter-item.u-display--none").not(".ft-hidden"); const itemsToShow = hiddenItems.slice(0, 8); if (itemsToShow.length > 0) { const animatedCards = itemsToShow.find(".js-card-animate").get(); if (animatedCards.length > 0) { gsap.set(animatedCards, { opacity: 0, y: 12, filter: "blur(0.5px)", }); } itemsToShow.removeClass("u-display--none"); const filterContainer = $(".js-filter-container"); try { if (filterContainer.data("isotope")) { filterContainer.isotope("layout"); } } catch (error) {} if (animatedCards.length > 0) { gsap.to(animatedCards, { opacity: 1, y: 0, filter: "blur(0px)", duration: 0.4, ease: "power2.out", stagger: 0.04, }); } $(".js-button-load-more") .blur() .removeClass("active focus"); if (hiddenItems.length <= 8) { $(".js-button-load-more").hide(); } } }); } /* ========================================================================== Optional: Swiper timeline with horizontal scroll/drag behavior ========================================================================== */ /** * The bundle initializes a horizontal Swiper timeline. * * Requires Swiper and Navigation module. * * In the original minified code: * - fl = Swiper * - ml = Navigation module */ function initTimelineSwiper() { if (typeof Swiper === "undefined") { console.warn("Swiper is not available."); return; } // If using Swiper modules globally, adjust as needed. // Swiper.use([Navigation]); new Swiper(".js-timeline", { slidesPerView: 1, spaceBetween: "-10%", breakpoints: { 640: { slidesPerView: 2, }, 768: { slidesPerView: 3, }, 1024: { slidesPerView: 4, }, 1200: { slidesPerView: 5, }, }, direction: "horizontal", freeMode: true, navigation: { nextEl: ".swiper-button-next", prevEl: ".swiper-button-prev", }, }); } /* ========================================================================== Optional: Posts slider horizontal drag/scroll behavior ========================================================================== */ class PostsSlider { constructor() { this.sliders = document.querySelectorAll(".js-posts-slider"); this.swiperInstances = []; this.init(); } init() { if (!this.sliders.length) return; if (typeof Swiper === "undefined") { console.warn("Swiper is not available."); return; } // If using Swiper modules globally, adjust as needed. // Swiper.use([Navigation]); this.sliders.forEach((slider) => { const container = slider.querySelector(".js-posts-slider-container"); if (!container) return; const prevButton = slider.querySelector(".js-posts-slider-prev"); const nextButton = slider.querySelector(".js-posts-slider-next"); const swiper = new Swiper(container, { slidesPerView: "auto", spaceBetween: 0, grabCursor: true, watchSlidesProgress: true, wrapperClass: "js-posts-slider-wrapper", slideClass: "js-posts-slider-card", navigation: { nextEl: nextButton, prevEl: prevButton, }, on: { init: function () { if (prevButton) { prevButton.classList.add("swiper-button-disabled"); prevButton.setAttribute("disabled", "disabled"); } }, slideChange: function () { if (prevButton) { if (this.isBeginning) { prevButton.classList.add("swiper-button-disabled"); prevButton.setAttribute("disabled", "disabled"); } else { prevButton.classList.remove("swiper-button-disabled"); prevButton.removeAttribute("disabled"); } } if (nextButton) { if (this.isEnd) { nextButton.classList.add("swiper-button-disabled"); nextButton.setAttribute("disabled", "disabled"); } else { nextButton.classList.remove("swiper-button-disabled"); nextButton.removeAttribute("disabled"); } } }, }, }); this.swiperInstances.push(swiper); }); } } /* ========================================================================== Main initializer ========================================================================== */ function initExtractedScrollFunctionality() { cookieConsentScroll.init(); initSmoothAnchorScrolling(); initGsapScrollAnimations(); initLoadMoreScrollRelatedAnimation(); initTimelineSwiper(); new PostsSlider(); } /* ========================================================================== DOM ready ========================================================================== */ document.addEventListener("DOMContentLoaded", () => { initExtractedScrollFunctionality(); }); Point72, L.P. and its affiliates and our third-party partners use cookies and similar technologies to view and retain your site interactions to perform analytics, enable site functionality and assist our marketing efforts exclusively for recruiting purposes. 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=u)&&Object.keys(t.O).every(function(r){return t.O[r](e[a])})?e.splice(a--,1):(f=!1,u0&&r[s-1][2]>u;s--)r[s]=r[s-1];r[s]=[e,o,u]},t.n=function(r){var n=r&&r.__esModule?function(){return r.default}:function(){return r};return t.d(n,{a:n}),n},t.d=function(r,n){for(var e in n)t.o(n,e)&&!t.o(r,e)&&Object.defineProperty(r,e,{enumerable:!0,get:n[e]})},t.o=function(r,n){return Object.prototype.hasOwnProperty.call(r,n)},function(){var r={666:0};t.O.j=function(n){return 0===r[n]};var n=function(n,e){var o,u,i=e[0],f=e[1],a=e[2],c=0;if(i.some(function(n){return 0!==r[n]})){for(o in f)t.o(f,o)&&(t.m[o]=f[o]);if(a)var s=a(t)}for(n&&n(e);c
Research Engineer, Knowledge Graph Intelligence
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Experience
Experienced Professionals
Location
New York
Focus
Compliance
Business
Point72
A Career with Point72’s Surveillance Team
Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.
What you’ll do
As a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:
- Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.
- Work with sparse data and apply techniques to improve model accuracy and generalization.
- Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
- Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
- Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.
What’s required
- PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.
- 6+ years of experience building ML models and developing algorithms.
- Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.
- Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.
- Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
- Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
- Experience with data evaluation techniques, model explainability, and error analysis.
- Experience working in a Linux environment.
- Commitment to the highest ethical standards.
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Fully-paid health care benefits
- Generous parental and family leave policies
- Mental and physical wellness programs
- Volunteer opportunities
- Non-profit matching gift program
- Support for employee-led affinity groups representing women, minorities and the LGBT+ community
- Tuition assistance
- A 401(k) savings program with an employer match and more
About Point72
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
The annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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A Career with Point72’s Surveillance Team
\nPoint72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.
What you’ll do
\nAs a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:
- Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.
- Work with sparse data and apply techniques to improve model accuracy and generalization.
- Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
- Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
- Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.
What’s required
\n- PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.
- 6+ years of experience building ML models and developing algorithms.
- Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.
- Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.
- Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
- Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
- Experience with data evaluation techniques, model explainability, and error analysis.
- Experience working in a Linux environment.
- Commitment to the highest ethical standards.
We take care of our people
\nWe invest in our people, their careers, their health, and their well-being. When you work here, we provide:
\n- Fully-paid health care benefits
- Generous parental and family leave policies
- Mental and physical wellness programs
- Volunteer opportunities
- Non-profit matching gift program
- Support for employee-led affinity groups representing women, minorities and the LGBT+ community
- Tuition assistance
- A 401(k) savings program with an employer match and more
About Point72
\nPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
The annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations. \u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003EWhat you’ll do\u003C/h3\u003E\\n\u003Cp\u003EAs a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. 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Specifically, you will:\u003C/p\u003E\u003Cp\u003E\u003Cbr\u003E\u003C/p\u003E\u003Cul\u003E\u003Cli\u003EContribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.\u003C/li\u003E\u003Cli\u003EImplement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.\u003C/li\u003E\u003Cli\u003EWork with sparse data and apply techniques to improve model accuracy and generalization.\u003C/li\u003E\u003Cli\u003EConduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.\u003C/li\u003E\u003Cli\u003ECollaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.\u003C/li\u003E\u003Cli\u003EStay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWhat’s required\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003EPhD, master\'s degree, or 4+ years of CS, CE, ML or related field experience.\u003C/li\u003E\u003Cli\u003E6+ years of experience building ML models and developing algorithms.\u003C/li\u003E\u003Cli\u003EStrong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.\u003C/li\u003E\u003Cli\u003EPrior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.\u003C/li\u003E\u003Cli\u003EExpertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.\u003C/li\u003E\u003Cli\u003ESolid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.\u003C/li\u003E\u003Cli\u003EExperience with data evaluation techniques, model explainability, and error analysis.\u003C/li\u003E\u003Cli\u003EExperience working in a Linux environment.\u003C/li\u003E\u003Cli\u003ECommitment to the highest ethical standards.\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWe take care of our people\u003C/h3\u003E\\n\u003Cp\u003EWe invest in our people, their careers, their health, and their well-being. 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Research Engineer, Knowledge Graph Intelligence
at Point72
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Research Engineer, Knowledge Graph Intelligence
at Point72
Mid LevelNo visa sponsorshipPython
Posted 21 hours ago
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- Compensation
- $175,000 – $275,000 USD
- City
- Country
- United States
Currency: $ (USD)
**Research Engineer, Knowledge Graph Intelligence**, drives AI-driven graph insights. Develops graphs, models data relationships, optimizes search & recommendation systems. Required: 5+ years' graph data experience, proficient in Neo4j, spark, machine learning algorithms, and Python. Experience with knowledge graphs and/or graph neural networks is a plus. M.S. or Ph.D. in Computer Science, Mathematics, or related field.
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Research Engineer, Knowledge Graph Intelligence Career
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","title":"Research Engineer, Knowledge Graph Intelligence","@type":"JobPosting","@context":"http://schema.org/"} CSJobDetailModule.init('{\"lastModifiedDateFormatted\":\"2026-06-25\",\"job\":{\"attributes\":{\"type\":\"Job__c\",\"url\":\"/services/data/v67.0/sobjects/Job__c/a03Vo00001mBpXjIAK\"},\"Id\":\"a03Vo00001mBpXjIAK\",\"Name\":\"Research Engineer, Knowledge Graph Intelligence\",\"Assigned_Internal_Recruiter__c\":\"005Vo00000XyPLsIAN\",\"Job_Code__c\":\"IVS-0015003\",\"Experience__c\":\"Experienced Professionals\",\"Company__c\":\"001j000000VbgAOAAZ\",\"Posted_Location__c\":\"New York\",\"Area__c\":\"Legal & Compliance;Technology & Engineering\",\"Team__c\":\"Compliance\",\"Job_Description_External__c\":\"\u003Ch3\u003EA Career with Point72’s Surveillance Team\u003C/h3\u003E\\n\u003Cp\u003EPoint72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. 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When you work here, we provide:\u003C/p\u003E\\n\u003Cul\u003E\u003Cli\u003EFully-paid health care benefits\u003C/li\u003E\u003Cli\u003EGenerous parental and family leave policies\u003C/li\u003E\u003Cli\u003EMental and physical wellness programs\u003C/li\u003E\u003Cli\u003EVolunteer opportunities\u003C/li\u003E\u003Cli\u003ENon-profit matching gift program\u003C/li\u003E\u003Cli\u003ESupport for employee-led affinity groups representing women, minorities and the LGBT+ community\u003C/li\u003E\u003Cli\u003ETuition assistance\u003C/li\u003E\u003Cli\u003EA 401(k) savings program with an employer match and more\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EAbout Point72\u003C/h3\u003E\\n\u003Cp\u003EPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit \u003Ca href=\\\"https://www.Point72.com/working-here\\\\\\\" target=\\\"_blank\\\"\u003Ewww.Point72.com/working-here\u003C/a\u003E\u003C/p\u003E\u003Cbr\u003E\u003Cp\u003EThe annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. 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} .o-button-hamburger__line:nth-child(3) { top: calc( (var(--p72-hamburger-line-spacing) + var(--p72-hamburger-line-height)) * 2 ); } /* ========================================================= Hamburger Active Animation Triggered by .c-menu-mobile-is-active ========================================================= */ .c-menu-mobile-is-active .o-button-hamburger__line:first-child { top: 50%; transform: rotate(45deg); } .c-menu-mobile-is-active .o-button-hamburger__line:nth-child(2) { opacity: 0; } .c-menu-mobile-is-active .o-button-hamburger__line:nth-child(3) { top: 50%; transform: rotate(-45deg); } /** * Extracted scroll-related functionality from the bundled app. * * Requires: * - GSAP * - ScrollTrigger * - Optional: jQuery if using the jQuery-based class add below * * If you are using ES modules: * * import gsap from "gsap"; * import ScrollTrigger from "gsap/ScrollTrigger"; * * gsap.registerPlugin(ScrollTrigger); */ /* ========================================================================== Cookie consent scroll/resize height tracking ========================================================================== */ const COOKIE_NOTICE_KEY = "p72_cookie_notice_dismissed"; const cookieConsentScroll = { _raf: null, _scrollBound: false, _onScroll: null, isDismissed() { try { return sessionStorage.getItem(COOKIE_NOTICE_KEY) === "1"; } catch (error) { return false; } }, setDismissed() { try { sessionStorage.setItem(COOKIE_NOTICE_KEY, "1"); } catch (error) {} }, showBanner() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { banner.classList.remove("is-hidden"); banner.classList.add("is-visible"); this.updateHeightVar(); this.bindScroll(); } }, hideBanner() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { banner.classList.remove("is-visible"); banner.classList.add("is-hidden"); this.unbindScroll(); this.updateHeightVar(); } }, updateHeightVar() { const banner = document.querySelector(".js-cookie-consent"); let height = 0; if (banner && !banner.classList.contains("is-hidden")) { const rect = banner.getBoundingClientRect(); height = Math.min( Math.max(rect.bottom, 0), banner.offsetHeight ); } document.documentElement.style.setProperty( "--p72-cookie-consent-height", `${height}px` ); }, onScroll() { if (!this._raf) { this._raf = window.requestAnimationFrame(() => { this._raf = null; this.updateHeightVar(); }); } }, bindScroll() { if (!this._scrollBound) { this._scrollBound = true; this._onScroll = this.onScroll.bind(this); window.addEventListener("scroll", this._onScroll, { passive: true, }); window.addEventListener("resize", this._onScroll, { passive: true, }); } }, unbindScroll() { if (this._scrollBound) { this._scrollBound = false; window.removeEventListener("scroll", this._onScroll); window.removeEventListener("resize", this._onScroll); } }, observeHeight() { const banner = document.querySelector(".js-cookie-consent"); if (!banner || typeof ResizeObserver === "undefined") return; new ResizeObserver(() => this.updateHeightVar()).observe(banner); }, handleClose() { this.setDismissed(); this.hideBanner(); }, init() { const banner = document.querySelector(".js-cookie-consent"); if (banner) { if (this.isDismissed()) { this.updateHeightVar(); } else { this.showBanner(); } this.observeHeight(); } else { document.documentElement.style.setProperty( "--p72-cookie-consent-height", "0px" ); } }, }; /* ========================================================================== Smooth anchor scrolling with header offset ========================================================================== */ function getAnchorTarget(hash) { if (!hash || hash === "#") return null; const id = hash.startsWith("#") ? hash.substring(1) : hash; let target = document.getElementById(id); if (!target) { try { target = document.querySelector(hash); } catch (error) { return null; } } return target; } function scrollToElementWithHeaderOffset(element) { const headerHeight = parseInt( getComputedStyle(document.documentElement) .getPropertyValue("--p72-header-height") ) || 0; const top = element.getBoundingClientRect().top + window.pageYOffset - headerHeight; window.scrollTo({ top, behavior: "smooth", }); } function initSmoothAnchorScrolling() { document.addEventListener("click", function (event) { const link = event.target.closest( 'a[href^="#"]:not([href="#"])' ); if (!link) return; const href = link.getAttribute("href"); const target = getAnchorTarget(href); if (target) { event.preventDefault(); scrollToElementWithHeaderOffset(target); if (history.pushState) { history.pushState(null, null, href); } } }); if (window.location.hash) { setTimeout(() => { const target = getAnchorTarget(window.location.hash); if (target) { scrollToElementWithHeaderOffset(target); } }, 100); } } /* ========================================================================== GSAP ScrollTrigger animations ========================================================================== */ function initGsapScrollAnimations() { if (typeof gsap === "undefined" || typeof ScrollTrigger === "undefined") { console.warn("GSAP or ScrollTrigger is not available."); return; } gsap.registerPlugin(ScrollTrigger); document.querySelectorAll(".js-gsap-trigger").forEach((trigger) => { /** * Fade in on scroll */ const fadeItems = trigger.querySelectorAll(".js-gsap-fade-in"); if (fadeItems.length > 0) { fadeItems.forEach((item, index) => { gsap.to(item, { opacity: 1, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, }); }); } /** * Scale in on scroll */ const scaleItems = trigger.querySelectorAll(".js-gsap-scale-in"); if (scaleItems.length > 0) { scaleItems.forEach((item, index) => { gsap.to(item, { scale: 1, opacity: 1, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, transformOrigin: "center center", }); }); } /** * Slide up on scroll */ const slideUpItems = trigger.querySelectorAll(".js-gsap-slide-in-up"); if (slideUpItems.length > 0) { slideUpItems.forEach((item, index) => { gsap.to(item, { opacity: 1, y: 0, duration: 0.8, ease: "power1.in", scrollTrigger: item, delay: 0.1 * index, }); }); } /** * Card entrance animation * * Note: * In the original bundle this is inside `.js-gsap-trigger`, * but it is not actually tied to ScrollTrigger. It runs immediately. */ const cards = trigger.querySelectorAll(".js-card-animate"); if (cards.length > 0) { console.log("Found cards to animate:", cards.length); gsap.set(cards, { opacity: 0, y: 12, filter: "blur(0.5px)", clearProps: "none", }); gsap.to(cards, { opacity: 1, y: 0, filter: "blur(0px)", duration: 0.3, ease: "power2.out", stagger: 0.03, delay: 0.05, }); } }); /** * Generic scroll class trigger */ gsap.utils.toArray(".u-scroll-animation").forEach((element) => { ScrollTrigger.create({ trigger: element, start: "top 90%", onEnter: () => { element.classList.add("u-scroll-animate"); }, }); }); } /* ========================================================================== Load-more card animation ========================================================================== */ function initLoadMoreScrollRelatedAnimation() { if (typeof jQuery === "undefined") { console.warn("jQuery is not available."); return; } if (typeof gsap === "undefined") { console.warn("GSAP is not available."); return; } const $ = jQuery; $(".js-button-load-more").on("click", () => { const hiddenItems = $(".js-filter-item.u-display--none").not(".ft-hidden"); const itemsToShow = hiddenItems.slice(0, 8); if (itemsToShow.length > 0) { const animatedCards = itemsToShow.find(".js-card-animate").get(); if (animatedCards.length > 0) { gsap.set(animatedCards, { opacity: 0, y: 12, filter: "blur(0.5px)", }); } itemsToShow.removeClass("u-display--none"); const filterContainer = $(".js-filter-container"); try { if (filterContainer.data("isotope")) { filterContainer.isotope("layout"); } } catch (error) {} if (animatedCards.length > 0) { gsap.to(animatedCards, { opacity: 1, y: 0, filter: "blur(0px)", duration: 0.4, ease: "power2.out", stagger: 0.04, }); } $(".js-button-load-more") .blur() .removeClass("active focus"); if (hiddenItems.length <= 8) { $(".js-button-load-more").hide(); } } }); } /* ========================================================================== Optional: Swiper timeline with horizontal scroll/drag behavior ========================================================================== */ /** * The bundle initializes a horizontal Swiper timeline. * * Requires Swiper and Navigation module. * * In the original minified code: * - fl = Swiper * - ml = Navigation module */ function initTimelineSwiper() { if (typeof Swiper === "undefined") { console.warn("Swiper is not available."); return; } // If using Swiper modules globally, adjust as needed. // Swiper.use([Navigation]); new Swiper(".js-timeline", { slidesPerView: 1, spaceBetween: "-10%", breakpoints: { 640: { slidesPerView: 2, }, 768: { slidesPerView: 3, }, 1024: { slidesPerView: 4, }, 1200: { slidesPerView: 5, }, }, direction: "horizontal", freeMode: true, navigation: { nextEl: ".swiper-button-next", prevEl: ".swiper-button-prev", }, }); } /* ========================================================================== Optional: Posts slider horizontal drag/scroll behavior ========================================================================== */ class PostsSlider { constructor() { this.sliders = document.querySelectorAll(".js-posts-slider"); this.swiperInstances = []; this.init(); } init() { if (!this.sliders.length) return; if (typeof Swiper === "undefined") { console.warn("Swiper is not available."); return; } // If using Swiper modules globally, adjust as needed. // Swiper.use([Navigation]); this.sliders.forEach((slider) => { const container = slider.querySelector(".js-posts-slider-container"); if (!container) return; const prevButton = slider.querySelector(".js-posts-slider-prev"); const nextButton = slider.querySelector(".js-posts-slider-next"); const swiper = new Swiper(container, { slidesPerView: "auto", spaceBetween: 0, grabCursor: true, watchSlidesProgress: true, wrapperClass: "js-posts-slider-wrapper", slideClass: "js-posts-slider-card", navigation: { nextEl: nextButton, prevEl: prevButton, }, on: { init: function () { if (prevButton) { prevButton.classList.add("swiper-button-disabled"); prevButton.setAttribute("disabled", "disabled"); } }, slideChange: function () { if (prevButton) { if (this.isBeginning) { prevButton.classList.add("swiper-button-disabled"); prevButton.setAttribute("disabled", "disabled"); } else { prevButton.classList.remove("swiper-button-disabled"); prevButton.removeAttribute("disabled"); } } if (nextButton) { if (this.isEnd) { nextButton.classList.add("swiper-button-disabled"); nextButton.setAttribute("disabled", "disabled"); } else { nextButton.classList.remove("swiper-button-disabled"); nextButton.removeAttribute("disabled"); } } }, }, }); this.swiperInstances.push(swiper); }); } } /* ========================================================================== Main initializer ========================================================================== */ function initExtractedScrollFunctionality() { cookieConsentScroll.init(); initSmoothAnchorScrolling(); initGsapScrollAnimations(); initLoadMoreScrollRelatedAnimation(); initTimelineSwiper(); new PostsSlider(); } /* ========================================================================== DOM ready ========================================================================== */ document.addEventListener("DOMContentLoaded", () => { initExtractedScrollFunctionality(); }); Point72, L.P. and its affiliates and our third-party partners use cookies and similar technologies to view and retain your site interactions to perform analytics, enable site functionality and assist our marketing efforts exclusively for recruiting purposes. 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=u)&&Object.keys(t.O).every(function(r){return t.O[r](e[a])})?e.splice(a--,1):(f=!1,u0&&r[s-1][2]>u;s--)r[s]=r[s-1];r[s]=[e,o,u]},t.n=function(r){var n=r&&r.__esModule?function(){return r.default}:function(){return r};return t.d(n,{a:n}),n},t.d=function(r,n){for(var e in n)t.o(n,e)&&!t.o(r,e)&&Object.defineProperty(r,e,{enumerable:!0,get:n[e]})},t.o=function(r,n){return Object.prototype.hasOwnProperty.call(r,n)},function(){var r={666:0};t.O.j=function(n){return 0===r[n]};var n=function(n,e){var o,u,i=e[0],f=e[1],a=e[2],c=0;if(i.some(function(n){return 0!==r[n]})){for(o in f)t.o(f,o)&&(t.m[o]=f[o]);if(a)var s=a(t)}for(n&&n(e);c
Research Engineer, Knowledge Graph Intelligence
Apply Now
Experience
Experienced Professionals
Location
New York
Focus
Compliance
Business
Point72
A Career with Point72’s Surveillance Team
Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.
What you’ll do
As a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:
- Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.
- Work with sparse data and apply techniques to improve model accuracy and generalization.
- Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
- Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
- Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.
What’s required
- PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.
- 6+ years of experience building ML models and developing algorithms.
- Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.
- Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.
- Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
- Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
- Experience with data evaluation techniques, model explainability, and error analysis.
- Experience working in a Linux environment.
- Commitment to the highest ethical standards.
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Fully-paid health care benefits
- Generous parental and family leave policies
- Mental and physical wellness programs
- Volunteer opportunities
- Non-profit matching gift program
- Support for employee-led affinity groups representing women, minorities and the LGBT+ community
- Tuition assistance
- A 401(k) savings program with an employer match and more
About Point72
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
The annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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A Career with Point72’s Surveillance Team
\nPoint72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.
What you’ll do
\nAs a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:
- Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.
- Work with sparse data and apply techniques to improve model accuracy and generalization.
- Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
- Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
- Stay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.
What’s required
\n- PhD, master's degree, or 4+ years of CS, CE, ML or related field experience.
- 6+ years of experience building ML models and developing algorithms.
- Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.
- Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.
- Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
- Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
- Experience with data evaluation techniques, model explainability, and error analysis.
- Experience working in a Linux environment.
- Commitment to the highest ethical standards.
We take care of our people
\nWe invest in our people, their careers, their health, and their well-being. When you work here, we provide:
\n- Fully-paid health care benefits
- Generous parental and family leave policies
- Mental and physical wellness programs
- Volunteer opportunities
- Non-profit matching gift program
- Support for employee-led affinity groups representing women, minorities and the LGBT+ community
- Tuition assistance
- A 401(k) savings program with an employer match and more
About Point72
\nPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
The annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
","title":"Research Engineer, Knowledge Graph Intelligence","@type":"JobPosting","@context":"http://schema.org/"} CSJobDetailModule.init('{\"lastModifiedDateFormatted\":\"2026-06-25\",\"job\":{\"attributes\":{\"type\":\"Job__c\",\"url\":\"/services/data/v67.0/sobjects/Job__c/a03Vo00001mBpXjIAK\"},\"Id\":\"a03Vo00001mBpXjIAK\",\"Name\":\"Research Engineer, Knowledge Graph Intelligence\",\"Assigned_Internal_Recruiter__c\":\"005Vo00000XyPLsIAN\",\"Job_Code__c\":\"IVS-0015003\",\"Experience__c\":\"Experienced Professionals\",\"Company__c\":\"001j000000VbgAOAAZ\",\"Posted_Location__c\":\"New York\",\"Area__c\":\"Legal & Compliance;Technology & Engineering\",\"Team__c\":\"Compliance\",\"Job_Description_External__c\":\"\u003Ch3\u003EA Career with Point72’s Surveillance Team\u003C/h3\u003E\\n\u003Cp\u003EPoint72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations. \u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003EWhat you’ll do\u003C/h3\u003E\\n\u003Cp\u003EAs a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of NLP, while also conducting novel research as required. Specifically, you will:\u003C/p\u003E\u003Cp\u003E\u003Cbr\u003E\u003C/p\u003E\u003Cul\u003E\u003Cli\u003EContribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.\u003C/li\u003E\u003Cli\u003EImplement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements.\u003C/li\u003E\u003Cli\u003EWork with sparse data and apply techniques to improve model accuracy and generalization.\u003C/li\u003E\u003Cli\u003EConduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.\u003C/li\u003E\u003Cli\u003ECollaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.\u003C/li\u003E\u003Cli\u003EStay up to date with the latest advancements in natural language processing and machine learning, applying new techniques as needed.\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWhat’s required\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003EPhD, master\'s degree, or 4+ years of CS, CE, ML or related field experience.\u003C/li\u003E\u003Cli\u003E6+ years of experience building ML models and developing algorithms.\u003C/li\u003E\u003Cli\u003EStrong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications.\u003C/li\u003E\u003Cli\u003EPrior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation.\u003C/li\u003E\u003Cli\u003EExpertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.\u003C/li\u003E\u003Cli\u003ESolid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.\u003C/li\u003E\u003Cli\u003EExperience with data evaluation techniques, model explainability, and error analysis.\u003C/li\u003E\u003Cli\u003EExperience working in a Linux environment.\u003C/li\u003E\u003Cli\u003ECommitment to the highest ethical standards.\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWe take care of our people\u003C/h3\u003E\\n\u003Cp\u003EWe invest in our people, their careers, their health, and their well-being. When you work here, we provide:\u003C/p\u003E\\n\u003Cul\u003E\u003Cli\u003EFully-paid health care benefits\u003C/li\u003E\u003Cli\u003EGenerous parental and family leave policies\u003C/li\u003E\u003Cli\u003EMental and physical wellness programs\u003C/li\u003E\u003Cli\u003EVolunteer opportunities\u003C/li\u003E\u003Cli\u003ENon-profit matching gift program\u003C/li\u003E\u003Cli\u003ESupport for employee-led affinity groups representing women, minorities and the LGBT+ community\u003C/li\u003E\u003Cli\u003ETuition assistance\u003C/li\u003E\u003Cli\u003EA 401(k) savings program with an employer match and more\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EAbout Point72\u003C/h3\u003E\\n\u003Cp\u003EPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit \u003Ca href=\\\"https://www.Point72.com/working-here\\\\\\\" target=\\\"_blank\\\"\u003Ewww.Point72.com/working-here\u003C/a\u003E\u003C/p\u003E\u003Cbr\u003E\u003Cp\u003EThe annual base salary range for this role is $175,000-$275,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.\u003C/p\u003E\u003Cbr\u003E\",\"Japanese_Job_Description_External__c\":\"\u003Cbr\u003E\u003Cbr\u003E\u003Cbr\u003E\",\"Transcript_Optional__c\":false,\"RecordTypeId\":\"012j0000000tcfoAAA\",\"Apply_Now_URL__c\":\"https://boards.greenhouse.io/point72/jobs/8531773002?gh_jid=8531773002\",\"Type__c\":\"Full Time\",\"LastModifiedDate\":\"2026-06-25T14:21:16.000+0000\",\"Location__c\":\"New York, New York\",\"Company__r\":{\"attributes\":{\"type\":\"Account\",\"url\":\"/services/data/v67.0/sobjects/Account/001j000000VbgAOAAZ\"},\"Business__c\":\"Point72\",\"Name\":\"Point72 Asset Management, L.P.\",\"Id\":\"001j000000VbgAOAAZ\",\"RecordTypeId\":\"012j0000000tIlgAAE\"},\"RecordType\":{\"attributes\":{\"type\":\"RecordType\",\"url\":\"/services/data/v67.0/sobjects/RecordType/012j0000000tcfoAAA\"},\"DeveloperName\":\"Investment_Services\",\"Name\":\"Investment Services\",\"Id\":\"012j0000000tcfoAAA\"}},\"friendlyJobName\":\"research-engineer-knowledge-graph-intelligence\",\"formattedTeam\":\"Compliance\",\"formattedLocation\":\"New York\",\"formattedArea\":\"Legal & Compliance | Technology & Engineering\"}');
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