Saumik Dana -

Saumik Dana

Saumik Dana's Road Trips

About Me

I am a volatility trading and index rebalancing quant at a CT based buy side firm. I hold a PhD from University of Texas at Austin. I am a US permanent resident.

Technical Expertise

Programming & Tools

  • Python
  • Pandas
  • Poetry Package Manager
  • Git & Version Control

Financial Analytics

  • Options Trading Strategies
  • Volatility Modeling (SVI, SSVI)
  • Delta Hedging
  • Portfolio Optimization

Machine Learning

  • XGBoost & Random Forest
  • Genetic Algorithms
  • SHAP Feature Importance
  • Monte Carlo Simulations

Mathematical Methods

  • Black-Scholes PDE
  • Convex Optimization
  • Time Series Analysis
  • Statistical Modeling

Professional Experience

Feb 2024 - Present

Consultant, Asset Management Firm

Index Rebalancing: Implemented sophisticated rebalancing systems for geopolitical risk filtering with convex QP S&P 500 tracking error minimization. Delivered consistent 100-300bps alpha with 10-20% Sortino ratio outperformance.

Options Trading: Built comprehensive Python backtesting framework. Achieved Sharpe ratios exceeding 1.5 on index options and 40%+ CAGR on single stock options.

Sector Rotation: Developed greenfield sector rotation system for 11 SPDR ETFs with 50+ engineered features and bi-objective beta-neutral alpha maximizing optimizer.

Aug 2023 - Nov 2023

Computational Engineer, VISIE Inc.

Implemented Python code to control robotic arm of surgical navigation prototype. The CI/CD was done using Poetry. Played instrumental role in securing $8.2M Series A investment by enhancing precision in robotic control systems.

Aug 2022 - Mar 2023

Computational Lead, Sapientai LLC

Developed PDE discovery framework for stock prediction from cross-stock relationships using higher order derivative features and sparse greedy regression. Achieved robust forward prediction performance.

Education

PhD

University of Texas at Austin

Doctor of Philosophy in Engineering Mechanics

Other Projects

Shenanigans

Beer Montage Driver's View Montage