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Data Scientist, Quantitative Research
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ICE . Get AI-powered advice on this job and more exclusive features. 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 must be able 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 documentation and presentations to illustrate methods, techniques, and findings for individuals with diverse professional backgrounds. Manage large data sets and interpret diverse database architectures 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
Bachelors degree in Data Science/Analytics, Engineering, Mathematics, Statistics, or similar; Post Graduate degree preferred. Statistical programming experience in Python, R, MATLAB, C/C++, or Java. Working knowledge of SQL and experience 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. Additional Details
Employment type: Full-time Job function: Engineering and Information Technology Seniority level: Not Applicable #J-18808-Ljbffr
Data Scientist, Quantitative Research
role at
ICE . Get AI-powered advice on this job and more exclusive features. 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 must be able 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 documentation and presentations to illustrate methods, techniques, and findings for individuals with diverse professional backgrounds. Manage large data sets and interpret diverse database architectures 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
Bachelors degree in Data Science/Analytics, Engineering, Mathematics, Statistics, or similar; Post Graduate degree preferred. Statistical programming experience in Python, R, MATLAB, C/C++, or Java. Working knowledge of SQL and experience 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. Additional Details
Employment type: Full-time Job function: Engineering and Information Technology Seniority level: Not Applicable #J-18808-Ljbffr