Data Scientist, Global Quantitative Research at ICE in Atlanta, GA

Overview

Job Purpose

The Data Scientist will join the Quant Group which designs, implements, and supports enterprise quantitative models and systems. The primary role of this position will be to support the design and development of financial data models and provide data support for the Quant and Risk divisions. The role will use a variety of data science, analytics and engineering tools and techniques to solve diverse, data focused problems across the business. The candidate for this job must have the ability to work in a fast-paced environment, formulate and articulate solutions, defend assumptions and be highly detail oriented. This role requires frequent interaction with Quant Research, Risk Managers, Developers and Senior Management.

Responsibilities

• Perform data exploration and statistical analysis for quantitative research purposes
• Data preparation, validation, and visualization of various data sets such as time series of financial derivatives
• Build production quality, data driven software solutions to support data management and analysis
• Develop ETL applications to support core quant and risk team data requirements
• Diagnose and profile data issues and recommend ways to improve data reliability, efficiency, and quality
• Coordinate with quantitative research and business experts to develop and refine data management best practices, policies, and procedures
• Provide documentations and/or presentations to illustrate methods, techniques, and findings for individuals with diverse professional backgrounds
• Manage large data sets and interpret diverse database architecture across various platforms such as Oracle, Postgres, Snowflake, etc.
• Serve as a liaison between technology, operations, product management and the Financial Engineering teams
• Engage in innovative research tasks in the quantitative finance and data science field

Knowledge and Experience

• Master's degree in Data Science, Engineering, Mathematics, Statistics or similar field
• Statistical programming experience required, with strong preference for Python. Experience with R, MATLAB, C/C++ or Java is also valued
• Working knowledge of SQL and experience working with relational databases preferred
• Ability to work in a high-performance, high-velocity environment
• Strong analytical and organizational skills with acute attention to detail
• Strong communication skills
• Customer focused and results oriented
• Advanced Statistics knowledge related to Time Series preferred
• Experience with code versioning tools such as Git preferred
• Experience in Quantitative Finance and/or Financial Derivatives