Quantitative Software Engineer

Overview

As a Quantitative Risk Management (QRM) Software Engineer, you will play a critical role in developing and maintaining risk models used for margin, clearing fund, and stress testing. You’ll work at the intersection of quantitative finance and software engineering, building robust model infrastructure and tools that support risk analysis across financial products and derivatives. You’ll collaborate closely with quantitative analysts, model validators, business stakeholders, and engineering teams to implement new models, enhance existing ones, and ensure high-quality production deployment.

Responsibilities

• Design, implement, and maintain production-grade risk model software and supporting infrastructure.
• Develop quantitative models for pricing, risk management, and stress testing of financial instruments.
• Build and maintain model prototypes and testing tools using industry best practices.
• Conduct comprehensive quality assurance testing for model implementations, including unit testing, automation, and reference model creation.
• Present test plans and results to stakeholders and incorporate feedback from peers and validators.
• Participate in code reviews and contribute to model release testing, including margin impact analysis and production integration.
• Support large-scale model backtesting using historical data and analyze results.
• Provide integration support for applications consuming QRM libraries.
• Assist in launching new financial products and provide quantitative support to risk managers.
• Maintain and support numerical libraries and risk systems in production environments.
• Contribute to the development of internal tools including databases, ETLs, services, orchestration, and CI/CD pipelines.

Minimum Qualifications

• 6+ years of experience in quantitative finance or model development and testing.
• Strong foundation in financial mathematics, statistics, and numerical methods.
• Strong proficiency in Python and experience with scientific computing and automated testing frameworks.
• Solid understanding of financial markets and derivatives across equities, interest rates, and commodities.
• Experience with relational databases and SQL.

Preferred Qualifications

• Experience with distributed data systems and cloud-based infrastructure.
• Familiarity with Agile/SCRUM development methodologies.
• Proficiency in additional programming languages (e.g., Java, C++, R, shell scripting).
• Experience with version control and CI/CD tools (e.g., Git, GitHub, Jenkins).
• Knowledge of non-relational databases and big data technologies.
• Ability to critically evaluate model methodologies and validation approaches.