Point72 Asset Management is a global private investment asset management company managing the assets of its founder, Steven A. Cohen, and employees. The firm focuses primarily on discretionary long/short equity investing and makes significant quantitative and macro investments. It is headquartered in Stamford, Connecticut, maintains offices in Tokyo, Hong Kong, Singapore, London, Boston, and New York.
If you want to join a world-class investment management organization that operates in a fast-paced, dynamic environment and rewards talent with recognition and increased responsibility, then this is the right opportunity for you.
A Career with Point72's Market Intelligence Group
Market Intelligence is shaping Point72 for the future by combining the most innovative data sources, analysis, and investment tools with the Firm's traditional strengths at deep fundamental analysis of how companies and industries operate. Market Intelligence finds, tests, analyzes, and models alternative data; conducts deep fundamental research; and helps our investment teams generate alpha-producing ideas using our data and research. We produce investment insights by using machine learning techniques, fundamental company analysis, macro and sell-side research, and quantitative methodologies.
As a Data Scientist, you will support an idea generator testing investment theses using alternative data and building models to execute on the results of that research.
* Test research hypotheses and assumptions of researchers * Pull data from disparate sources * Design and validate models that transform data into actionable insights * Identify and deploy statistical, machine learning, and deep learning methods that strike the right balance between predictive power and robustness * Write efficient, modular, and dependable code, packages, libraries, and scripts * Iterate quickly to test the additive impact of new data and research findings on alpha generation * Document all work extensively * Stay abreast of new research
* Ph.D. (preferred) or M.S. in a technical field with an applied or experimental component * 3+ years of experience in a relevant field researching real-world data problems (though not necessarily in finance) * Extensive experience developing algorithms and production-grade code * Strong programming skills in Python and SQL/NoSQL * Experience with cloud infrastructures * Strong written and verbal communication skills and a proven ability to collaborate with others
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