Data Scientist
About The Position
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 Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.
Requirements
- BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
- Programming in Python (or a comparable language) and working knowledge of SQL.
- Strong analytical and quantitative skills.
- Willingness to take ownership of their work.
- Ability to work both independently and collaboratively within a team.
- Strong desire to deliver high quality results in a timely fashion.
- High attention to detail.
- Commitment to the highest ethical standards.
Nice To Haves
- Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus
Responsibilities
- Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
- Generate novel ideas for enhanced proprietary data products.
- Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
- Transform firm approved raw datasets into robust features for our systematic models.
- Build analytical tools to supplement our shared research framework.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees
