Data Scientist, Global Quantitative Research

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