What You’ll Do
- Onboard, clean, evaluate, and structure new financial and alternative datasets
- Use AI agents to accelerate alpha research, hypothesis generation, and strategy testing
- Develop systematic investment strategies from research concept through validation
- Analyze performance, risk, robustness, and implementation constraints of research outputs
- Work with engineering to improve KelAI’s research workflows and agent capabilities
- Support forward deployment with hedge funds and institutional investors by translating real research workflows into product and research requirements
What We’re Looking For
- 3-5 years of experience in quantitative research, systematic investing, data science, or a related field
- Strong understanding of financial markets, alpha research, backtesting, and portfolio construction
- Experience working with large financial datasets and research pipelines
- Strong Python skills and ability to move independently from data exploration to tested research output
- Interest in applying AI agents to investment research and systematic strategy development
- Strong communication skills and ability to work with both technical teams and investment users
About KelAI
Founded by a former WorldQuant portfolio manager and Head of Event-Driven Systematic Strategies, KelAI is a YC-backed, venture-funded company building the autonomous alpha engine for hedge funds, traders, and institutional investors.
We help investment teams turn data, research, and market ideas into agentic quant workflows for signal generation, thesis monitoring, and better investment decisions.
Compensation: $150K - $200K
Experience: 3+ years
