Cubist Data Scientist

at  Point72

DESCRIPTION

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 group is looking for a Data Scientist to join our dedicated 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.
This exceptional individual will be a member of a small team of Data Scientists who 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.

REQUIREMENTS

• Ph.D. in computer science, mathematics, physics, statistics or another disciplines involving rigorous quantitative analysis techniques
• At least 1 year of experience as a Data Scientist, quantitative researcher or in a similar role
• Experience working with large data sets, including classification, regression, distribution analysis, and predictive modeling
• Experience applying statistical tests to large data sets
• Programming skills in SQL, TSQL, SQL Server or PL-SQL
• Programming skills in Python and at least one of C#, C++, or Java
• Financial industry experience preferred but not required
• Experience dealing with intraday, tick and order book data a plus
• Strong problem solving skills
• Intellectual curiosity and a love of learning
• Attention to detail and a love of process
• Strong oral and written communication skills
  Job ID 7045995002

• Identification of new data sets
• Engaging with vendors to understand characteristics of datasets
• Building processes and technology tools to ingest, tag and clean datasets
• Analysis of datasets to generate descriptive statistics and propose potential applications of data
• Research of potential “alpha signals” for presentation to Portfolio Managers
• Monitoring and enhancing the automated data collection and cleansing infrastructure
• Research on new technologies for improved data management and efficient retrieval