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Quantitative Researcher

at Point72

Mid LevelNo visa sponsorshipPython

Posted a day ago

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Compensation: $175,000 – $200,000 USD
City: Chicago
Country: United States

**Quantitative Researcher:** Leverage statistical models to analyze massive datasets. Develop predictive models, conduct A/B tests, and derive insights using SQL, Python, and R. ideally 3+ years of experience in similar roles. Collaborate cross-functionally to improve products and drive business growth.

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Quantitative Researcher Career

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P72 Careers - Header

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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); 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Quantitative Researcher

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Experience

Experienced Professionals

Location

New York | Chicago

Focus

Systematic Investing

Business

Cubist

About Cubist:

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role/Responsibilities:

Perform rigorous applied research to discover systematic anomalies in equities markets
Present actionable trading ideas and enhance existing strategies
Identify short term opportunities in the high frequency/intraday space
Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)
Contribute towards the team’s research tooling and its efficiency
Help establish a collaborative mindset and shared ownership

Requirements:

Bachelor’s degree or higher in mathematics, statistics, computer science, or similar quantitative discipline
3+ years of work experience in systematic alpha research in equities using high frequency/intraday data
Fluency in data science practices, e.g., feature engineering, signal combining
Technically comfortable handling large datasets
Comfortable coding in both C++ and Python in a Linux environment
Exposure working with cloud computing platforms such as AWS
Highly motivated and willing to take ownership of his/her work
Collaborative mindset with strong independent research ability
Commitment to the highest ethical standards

The annual base salary range for this role is $175,000-$200,000 (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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About Cubist:

Role/Responsibilities:

Perform rigorous applied research to discover systematic anomalies in equities markets
Present actionable trading ideas and enhance existing strategies
Identify short term opportunities in the high frequency/intraday space
Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)
Contribute towards the team’s research tooling and its efficiency
Help establish a collaborative mindset and shared ownership

Requirements:

Bachelor’s degree or higher in mathematics, statistics, computer science, or similar quantitative discipline
3+ years of work experience in systematic alpha research in equities using high frequency/intraday data
Fluency in data science practices, e.g., feature engineering, signal combining
Technically comfortable handling large datasets
Comfortable coding in both C++ and Python in a Linux environment
Exposure working with cloud computing platforms such as AWS
Highly motivated and willing to take ownership of his/her work
Collaborative mindset with strong independent research ability
Commitment to the highest ethical standards

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