Data Scientist, Financial Engineering

Key Skills

Java Programming, Finance, Oracle, Design, Python Programming, C++, Database, C Programming, SQL, Git, Data science techniques, Data Visualization, MATLAB Programming, Snowflake, ETL frameworks, Large data sets

Job Description

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, 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

• Bachelor’s degree in Data Science/Analytics, Engineering, Mathematics, Statistics or similar required; Post Graduate degree in Data Science, Engineering, Mathematics, Statistics or similar preferred
• Statistical programming experience in Python, R, MATLAB, C/C++ or Java
• Working knowledge of SQL and experience working with relational databases
• 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 in data visualization tools such as Tableau preferred
• Experience with code versioning tools such as Git preferred

Schedule

This role offers work from home flexibility of up to 2 days per week, and 3 days in our office located in Atlanta, GA.

Intercontinental Exchange, Inc. is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin or ancestry, age, disability or veteran status, or other protected status.