Cubist Senior Data Scientist
Point72ROLE
We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance.
Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.
As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments.
RESPONSIBILITIES
- Onboarding novel datasets from a huge variety of sources into our platform
- Building processes, tools and frameworks to ingest, clean and deliver datasets
- Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams
- Creation of in-house, value added, derived data products for consumption by investment teams
- Engaging with vendors and internal stakeholders to understand characteristics of datasets
- Partnering closely with investment teams to ensure their data requirements are met
- Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams
REQUIREMENTS
- PhD or Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis
- Strong programming skills in Python and SQL
- Experience working with AWS, Linux and Airflow preferred but not required
- 5+ years of experience as a Data Scientist or similar role
- Experience working with large data sets including predictive modeling
- Financial industry experience preferred but not required
- Strong organization, communication and interpersonal skills
- Intellectual curiosity and enthusiasm for learning
- Attention to detail and a love of processes
- Strong oral and written communication skills
- Ability to multitask and prioritize assignments
- Commitment to the highest ethical standards