JOB DESCRIPTION: Quantitative Research Analyst, Portfolio Management Team, SAC MultiQuant (New York City)

An established quantitative portfolio management team within SAC is looking for a research analyst to contribute to its core business and to develop new areas of expertise. The candidate should possess outstanding empirical research skills, expert-level knowledge of statistical and machine learning techniques, and competence in software development.

Role/Responsibilities:

• New strategy (alpha) development
• Improvement of existing strategies and portfolio optimization
• Order-submission logic and transaction-cost analysis
• Uncovering, processing, and analyzing orthogonal (non-market, non-traditional) datasets looking for predictive power
• Applying statistical and machine learning techniques to historical data, predictive signals, and trading strategies
• Proposing, implementing, and evaluating various “features” or signals in large, noisy, real-world datasets
• Continue to build up a library of machine learning algorithms and related tools to be applied to various facets of the business

Requirements:

• The ideal candidate will have a strong combination of software development skills, quantitative skills and some finance background.
• PhD (preferred) or MS in a quantitative discipline. We are looking for someone who will thrive in an academic-style research environment, able to conduct independent open-ended projects in a systematic fashion with clear deliverables.
• Development skills in C++ or Java required and will be tested. Strong Linux expertise required. Familiarity with Matlab/R strongly desired.
• Prior experience with advanced statistical or machine learning techniques (time series analysis, reinforcement learning, supervised and unsupervised learning, no-regret learning, graphical models, NLP, etc.) is required.
• Must have experience in applying above techniques to very large real-world datasets (historical prices and volumes, TAQ, real-time order book data, social media data, news feeds, fundamental data, etc.).
• Our group focuses on systematic trading in liquid instruments (global equities, and futures). Candidates with work experience or expertise in these areas will be preferred. Familiarity with market microstructure is a big plus.

The group’s research-driven methodology for finding new sources of profitability has occasionally led to academic publications that are illustrative of the nature of the group and the expectations of candidates; interested parties can search the web for the publications “Empirical Limitations on High Frequency Trading Profitability”, “Censored Exploration and the Dark Pool Problem”, “Reinforcement Learning for Optimized Trade Execution”, and “The Penn-Lehman Automated Trading Project”.

SAC is an Equal Opportunity Employer.  SAC is committed to the principles of equal employment opportunity for all employees and applicants for employment.  SAC complies with applicable, local, state and federal laws on the subject of equal employment opportunity

Please email your resume to minhua.zhang@sac.com.