Intercontinental Exchange
Data Scientist, Quantitative Research
Intercontinental Exchange, Atlanta, Georgia, United States, 30383
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
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 with code versioning tools such as Git preferred
Experience in Quantitative Finance and/or Financial Derivatives preferred
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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
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 with code versioning tools such as Git preferred
Experience in Quantitative Finance and/or Financial Derivatives preferred
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