Quantitative Strategist
Biography
Aastha Jain is a quantitative strategist at FR Global Macro (FRGM), where she designs and builds the firm's AI-powered research systems. Her work spans agentic LLM frameworks that accelerate market research and simulation engines for position sizing and risk, using AI as a force multiplier across the research process. She holds a B.Tech from IIT Delhi and was previously a Ph.D. researcher at Columbia University. Before that, she was a machine-learning researcher at Columbia working on multi-objective LLM alignment, an NLP research intern at Microsoft Research building adaptive retrieval systems deployed to Bing Search, and a researcher at the Tata Institute of Fundamental Research (TIFR) developing deep-learning methods for rare-event simulation. Her published research includes work on deep learning for rare-event simulation in diffusion processes (Winter Simulation Conference, IEEE) and machine-learning approaches to monsoon-rainfall prediction. At FRGM she connects modern machine learning and software engineering with systematic market research, turning unstructured problems into automated, repeatable tools for the desk.
Areas of Expertise
- AI / agentic LLM systems
- Quantitative strategy
- Machine learning research
- Simulation for sizing & risk
- Ph.D. researcher — Columbia University
- B.Tech — IIT Delhi
Prior Experience
- ML Researcher (multi-objective LLM alignment) — Columbia University
- NLP Research Intern (deployed to Bing Search) — Microsoft Research
- Researcher (deep learning for rare-event simulation) — TIFR
Education & Credentials
- Former Ph.D. researcher — Columbia University
- B.Tech — IIT Delhi
