Senior Quantitative Strategist/Data Scientist

New York, New York, United States

Ref#: POS-3619

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Two Sigma’s Global Execution Services group is looking for a Senior Quantitative Strategist/Data Scientist to both contribute and mentor other quants as we improve our existing and build our next-generation trading and execution platforms.  The group is dynamic, highly motivated, and acts with the enthusiasm of a well-funded startup within the larger firm. The role includes creating and improving the ability to predict market interactions; using that knowledge to build models, software, and trading tactics for equities and  FX within our next-generation execution platform; and identifying creative ways to improve the trading desks of our institutional clients.

Global Execution Services provides execution and trading consultation services to large institutional clients, preserving alpha through better execution across multiple asset classes.  We deliver bespoke value and quality-based execution solutions to our clients while leveraging and expanding the capabilities of Two Sigma’s trading expertise.  Our team brings together technical and analytical capabilities to grapple with difficult computational and data-related problems directly and implement efficient and innovative solutions. Our solutions include a combination of sophisticated knowledge of algorithms, statistics, and high-performance computing.

We are looking for a talented research lead who can direct and develop a book of research; apply and develop machine learning algorithms for financial datasets; understand the financial drivers of our business and drive research to find meaningful solutions; and guide intelligent but less experienced members of the team.  The candidate should have direct experience in trade scheduling, optimization, forecasting or tactic building. Use of or implementation of trading algorithms is a plus.

The Senior Quantitative Strategist/Data Scientist is responsible for driving research and improving the business by:

  • Designing and implementing strategic trading algorithms;

  • Building the tools and engines that help us to understand and explain the underlying data

  • Researching trading data and market data for features and insights

  • Providing research guidance and mentorship at both the process and technical level

Requirements Include:

  • At a minimum, a bachelor's degree in computer science, applied mathematics, or another technical discipline from a top university.

  • Graduate degree in a similar technical discipline highly desired

  • Strong numerical programming skills.

  • Experience working with large datasets; knowledge of machine learning techniques desired

  • Experience in a group responsible for production trading a plus

  • A background or interest in production level, real-time, and distributed applications is desired.

  • 7+ years of experience utilizing statistical modeling techniques (e.g. machine learning or signal processing) in several of the following: nonstationary time series, regression analysis, return prediction, trading algorithms