Industry not specified

Quantitative Researcher

at Point72

JuniorNo visa sponsorshipPython

Posted 21 hours ago

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Compensation: Not specified
City: Hong Kong
Country: Not specified

**Quantitative Researcher**: Analyze complex data using statistical methods. Develop predictive models using SQL and R, Python. Collaborate cross-functionally. Requires 3+ years' experience in quantitative research, strong statistical background (PhD/Masters preferred). Experience with machine learning and big data advantageous.

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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

Apply Now

Experience

Early Career

Location

Hong Kong

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:

The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance.

Responsibilities:

Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas.
Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization.
Maintaining and improving portfolio trading in production environments.

Requirements:

Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline.
2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus.
Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning.
Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas.
Ability to work both independently and collaboratively within a team.
Commitment to the highest ethical standards.

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About Cubist

Role:

Responsibilities:

Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas.
Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization.
Maintaining and improving portfolio trading in production environments.

Requirements:

Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline.
2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus.
Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning.
Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas.
Ability to work both independently and collaboratively within a team.
Commitment to the highest ethical standards.

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