Hinal Jajal

Bio

I am a Senior Research Scientist at Balyasny Asset Management on the Applied AI team, led by Peter Anderson and Charlie Flanagan. My work focuses on AI for investment research, including post-training language models for forecasting, retrieval over financial data, and research agents.

Previously, I completed an M.S. in Data Science at Harvard University and a B.S. in Applied Mathematics with Computing at UCLA.

Publications

Global Merger-Arbitrage Forecasting with Language Models

Hinal Jajal, Michal Mucha, Charles Sweat, Chris Pulman, Charlie Flanagan, Peter Anderson

International Conference on Machine Learning (ICML), 2026

paper case study

Reinforcement Learning on Dyads to Enhance Medication Adherence

Ziping Xu, Hinal Jajal, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Alexandra M. Psihogios, Pei-Yao Hung, Susan A. Murphy

Artificial Intelligence in Medicine (AIME), 2025

paper

A Deployed Online Reinforcement Learning Algorithm in an Oral Health Clinical Trial

Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy

AAAI Conference on Artificial Intelligence, 2025

paper

Resume

• Balyasny Asset Management 2025 - present

  Senior Research Scientist
  Researcher on the Applied AI team at a multi-strategy hedge fund. Work focuses on AI for investment research, including post-training language models for forecasting, retrieval over financial data, and research agents. Public work appears in ICML paper, OpenAI case study, and Business Insider article.
• Balyasny Asset Management Summer 2024

  AI Researcher Intern
  Worked within the Applied AI team, building an AI superforecasting agent, with a focus on fine-tuning, semantic search, and synthetic data generation.
• Harvard University 2023 - 2024

  M.S. in Data Science
  Research in online reinforcement learning for digital-health interventions in Susan Murphy's Statistical Reinforcement Learning Lab.
• Pegasystems Fall 2022

  Data Science Intern
  Worked on the Workforce Intelligence team, focusing on predictive modeling of employee burnout using large-scale time-series data.
• Schonfeld Strategic Advisors Summer 2022

  Business Analytics Intern
  Worked on business analytics for investment operations, building web-data pipelines and SQL/Power BI dashboards for expense, P&L, and risk monitoring.
• International Game Technology Spring 2022

  Data Analytics Intern
  Data science for gaming-market strategy, focusing on market penetration analysis and customer segmentation.
• AcuityMD Fall 2021

  Operations Analyst Intern
  Data operations for medical-education platform development.
• Swiss Re Summer 2021

  Actuarial Analyst Intern
  Actuarial analytics for reinsurance, with work across workflow automation, rate analysis, and portfolio reporting.
• UCLA 2019 - 2023

  B.S. in Applied Mathematics with Computing
  Research at the intersection of statistical modeling and computational social science, modeling state-level criminal sentencing with Phil Chodrow.

Acknowledgement

The design of this website is thanks to a template by Martin Saveski with modifications from Tatsunori Hashimoto.