Data Scientist, Global Quantitative Research

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
• Cook up data management best practices, policies, and procedures
• 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

Requirements

• 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
• 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