Quantitative AI Strategist
Global principal trading firm; parent of Cumberland (crypto market maker).
Chicago, Illinois, USA
About DRW
DRW (drw.com) is a Chicago-based global principal trading firm across asset classes; its crypto arm is Cumberland, a leading digital-asset market maker.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will work with trading desks to identify valuable AI use cases, turn desk needs into quantitative workflows, and prototype solutions from data retrieval and signal construction through backtesting, PnL simulation, testing, and risk analysis. You will write platform code and quantitative libraries, improve AI-powered market analysis, and support platform users.
Requirements
- Background in quantitative finance, financial engineering, applied mathematics, statistics, physics, computer science, or a related technical field
- 3-7 years of experience in a front-office quant, strategist, or quantitative research role
- Understanding of financial markets, pricing and risk methodologies, and PnL attribution
- Experience with internal analytics platforms or tools used by traders and researchers
- Experience with signal generation, backtesting, or systematic strategy development
- Strong Python programming skills
- Familiarity with Git and collaborative development workflows
- Familiarity with AI technologies and their application to quantitative workflows
- Experience building AI agents
- Excellent communication skills
- Strong problem-solving ability
- Ability to learn and adapt to new technologies
Responsibilities
- Work with trading desks and firm stakeholders to identify high-value platform use cases
- Determine the balance between AI autonomy and structured tooling
- Turn desk needs into quantitative problems and workflows
- Prototype and validate quantitative workflows end to end
- Define how AI interacts with data sources, analytics libraries, and desk tools
- Write platform code and quantitative libraries
- Improve the platform's market reasoning and financial data analysis
- Evaluate platform usage and drive measurable workflow improvements
- Engage stakeholders to discover use cases and adapt platform capabilities
- Identify new AI use cases and capabilities
- Diagnose user issues and support platform development
Benefits
- Group medical insurance
- Pharmacy insurance
- Dental insurance
- Vision insurance
- 401k with discretionary employer match
- Short-term disability insurance
- Long-term disability insurance
- Life insurance
- AD&D insurance
- Health savings accounts
- Flexible spending accounts
