Quantitative Risk Engineer

Quantitative Risk Engineer

Hedge Fund – New York, NY (Hybrid On-Site)

Total Comp: Base Cash Bonus for 2025/Buyout

About the Role

This role sits at the intersection of quantitative modeling, large-scale compute systems, and engineering, working closely with risk managers, quants, and portfolio teams to deliver high-quality, high-performance risk analytics. You will play a key role in evolving the firm’s risk technology stack—driving improvements in modeling, automation, data integration, and user experience while tackling complex challenges across diverse asset classes.

What You’ll Do

• Architect and implement scalable analytical frameworks enabling flexible, high-performance compute across large and complex financial datasets.
• Develop a deep quantitative understanding of portfolio and market risk to proactively anticipate analytical and tooling needs for the Risk team.
• Build and enhance risk and P&L analytics capabilities, delivering robust, reliable, and high-performance software solutions.
• Solve sophisticated engineering and quantitative problems through innovative, modern technology approaches.
• Enhance the usability, automation, and integration of risk systems across the firm, improving workflows and eliminating friction points for downstream users.
• Partner with quants, traders, and risk managers to translate analytical requirements into production-quality systems.
• Drive best practices in data consistency, modeling accuracy, and computational efficiency.

What’s Required

• 8 years of hands-on programming experience in Python, .NET and C#
• Bachelor’s degree in Computer Science, Mathematics, Physics, or a related quantitative/technical field.
• Proven experience integrating trading platforms with enterprise risk systems, including a strong understanding of ETL processes and handling large volumes of structured and unstructured financial data.
• Strong working knowledge of risk analytics—including Stress, VaR, P&L decomposition, and scenario-based methodologies—across multiple asset classes (e.g., Fixed Income, FX, Commodities, Credit, or Equities).
• Demonstrated ability to build, design, and deliver full end-to-end software solutions in a fast-paced, mission-critical environment.
• Advanced analytical and data-quality skills with exceptional attention to accuracy, consistency, and completeness.
• Excellent verbal and written communication skills; able to engage effectively with peers, quants, traders, and senior stakeholders.
• High ethical standards and a commitment to integrity in all aspects of engineering and data management.