Analyst, Global Quantitative Research

Overview

In this role, you will develop and support enterprise quantitative models and risk analytics for clearing houses, blending quantitative research with data science. You will build scalable data pipelines and production-ready software to enable model implementation and risk assessment across asset classes. You’ll collaborate with Risk, Technology, and senior stakeholders to advance data-driven solutions and innovative quantitative finance research, shaping risk management in a demanding, high-performance environment.

Responsibilities

• Lead research and development of margin, stress testing, and risk management models for clearing houses
• Perform quantitative risk analysis across asset classes (rates, equities, credit, commodities)
• Conduct data exploration, statistical analysis, and time series modeling for research
• Build production-quality, data-driven software for model implementation and analytics
• Develop ETL pipelines and data management tools for large-scale datasets
• Diagnose data issues and advise on data architecture and governance
• Define business requirements for model enhancements and data workflows
• Develop and maintain in-house quantitative research platforms and analytics tools
• Document methodologies and present findings to regulators, risk committees, and senior management
• Collaborate with technology teams for production integration of models and data systems
• Engage in innovative research in quantitative finance and data science

Key requirements

• Advanced degree (MSc or PhD) in a quantitative field
• Experience in quantitative finance or data science in financial institutions with a track record in model development or implementation
• Strong programming skills in Python and SQL; familiarity with R, MATLAB, C++, or Java preferred
• Working knowledge of relational databases (Oracle, Postgres, Snowflake) and Git
• Solid understanding of statistics, time series analysis, and derivatives pricing and risk management
• Ability to work under pressure in a high-performance environment with tight deadlines
• Excellent analytical, organizational, and communication skills; capable of articulating complex concepts to diverse audiences
• Customer-focused, results-oriented, and highly detail-oriented

• Excellent analytical and organizational skills
• Effective communication across technical and non-technical audiences
• Customer-focused and results-driven
• Python
• SQL
• R

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