Open to opportunities

tanmay goyal

@tanmaygoyal

Message

Quantitative researcher and trader building execution-aware index derivatives alpha.

India

Message

What I'm looking for

I’m looking to build execution-aware, short-horizon alpha for index derivatives—combining market microstructure signals, rigorous validation, and production-grade low-latency trading systems that improve real-world P&L and risk control.

I’m a Quantitative Researcher / Trader with 4+ years of experience in short-horizon alpha generation, index derivatives trading, and execution-aware strategy design. I’ve engineered 70+ market microstructure feature families and built predictive models (XGBoost, quantile models) for high-frequency NIFTY derivatives forecasting that directly support live trading and hedging decisions.

I optimize trading efficiency and risk using execution threshold tuning, dynamic sizing, and portfolio rebalancing—achieving 92.5% reduction in trading costs. I also build production-grade low-latency systems, bridging Python research to C++ deployment with ONNX Runtime, while delivering robust walk-forward validation and constraint-aware portfolio optimization (HiGHS) for delta, gamma, and vega.

Experience

Work history, roles, and key accomplishments

Current

Quantitative Researcher

Current

Minix Fintech LLP

Dec 2024 - Present (1 year 6 months)

Researched short-horizon alpha and execution-aware behavior for index option strategies using tick-level derivatives data. Reduced trading costs by 92.5% via execution threshold tuning, dynamic sizing, and built a HiGHS-based transaction-cost optimizer under delta, gamma, and vega constraints.

Short Horizon Alpha Generation Market Microstructure Execution Aware Strategy Design Python C#HiGHS Portfolio Optimization Tick Level Derivatives Data

Quantitative Trader

PsyQuant Research LLP

May 2023 - Nov 2024 (1 year 6 months)

Trained and deployed XGBoost mean and quantile models for short-horizon NIFTY prediction, integrating signals with production sizing and hedging logic. Built tick-level microstructure features and developed a C++ ONNX Runtime inference pipeline for scalable live trading.

Feature Engineering XGBoost Quantile Regression ONNX Runtime C++ Inference Pipeline Derivatives Forecasting

Quantitative Analyst

Dolat Capital

Nov 2021 - May 2023 (1 year 6 months)

Developed statistical and ML models for short-horizon trading in NIFTY and BankNifty options to enhance alpha generation. Performed tick-level return pattern analysis and refined execution parameters using simulations and trading diagnostics to improve robustness.

Options Trading predictive modeling Tick Level Data Analysis Robustness Python Market Microstructure

Machine Learning Engineer

Quantiphi Analytics

Apr 2021 - Nov 2021 (7 months)

Built and deployed end-to-end machine learning pipelines for financial services use cases, covering data preparation, feature engineering, model training, and cloud deployment. Supported model integration workflows from research to production.