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.

RESPONSIBILITIES

• 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

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