Quantitative AI Strategist

The ideal candidate will be able to

• Work directly with trading desks across asset classes and other stakeholders across the firm to identify high-value use cases for the platform.
• Determine the right balance between AI autonomy and structured tooling - deciding what the AI should reason through on its own, what instructions and domain knowledge it needs, and what purpose-built code it should call - and build accordingly.
• Work with front-office stakeholders to turn desk needs into well-defined quantitative problems/workflows, and collaborate with technology teams and quantitative researchers to deliver solutions.

Key Responsibilities

• Prototype and validate quantitative workflows end-to-end - from data retrieval and signal construction through to strategy evaluation, PnL simulation, testing, and risk/scenario analysis - while defining how the AI should interact with data sources, analytics libraries, desk-specific tools, etc., and work with engineers to deliver them as production platform capabilities.
• Write high-quality platform code and quantitative libraries - including code designed to be called and understood by AI, with clear interfaces, documentation, and instructions to AI.
• Enhance the platform's ability to reason about markets, interpret financial data, and produce reliable, contextually aware analysis across products and markets.
• Continuously evaluate how the platform is used, identify where it excels and where it falls short, and drive improvements that deliver measurable value to trading and research workflows.
• Engage with stakeholders across the firm - trading desks, risk management, researchers, new joiners, and others - to discover emerging use cases and adapt the platform's capabilities accordingly.
• Proactively identify new use cases and capabilities as AI technology evolves.
• Act as the first line of quantitative support for platform users - diagnosing issues, feeding insights back into platform development, and ensuring a high-quality user experience.

Qualification and Experience

• Background in quantitative finance, financial engineering, applied mathematics, statistics, physics, computer science, or a related technical field.
• 3-7 years' experience in a front-office quant, strategist, or quantitative research role, ideally with exposure to multiple asset classes.
• Solid understanding of financial markets, pricing/risk methodologies, and PnL attribution.
• Experience building or contributing to internal analytics platforms or tools used by traders and researchers.
• Experience with signal generation, backtesting, or systematic strategy development.
• Strong programming skills in Python. Familiarity with Git and collaborative development workflows.
• Familiarity with AI technologies and their application to quantitative workflows is a strong plus.
• Experience building AI agents is a strong plus.
• Excellent communication skills - able to engage directly with trading desks to understand their needs, formalize them into quantitative specifications, and collaborate effectively with software engineers.
• Strong problem-solving ability, intellectual curiosity, and comfort working across team boundaries in a fast-paced trading environment.
• Strong ability to quickly learn and adapt to new technologies - particularly important given the rapid pace of development in AI.

Pay and benefits

The annual base salary range for this position is $175k to $250k depending on the candidate's experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.