Ankush Garg

About Ankush Garg

I am a Quantitative Researcher and Financial ML Consultant working with multiple long-term clients across trading, analytics, and applied machine learning domains.I specialize in designing and validating systematic trading strategies, reinforcement learning-based decision systems, and production-grade ML pipelines with a strong focus on risk-adjusted performance.Quantitative Trading & Backtesting• Built systematic equity & securities trading strategies using QuantConnect (Lean engine)• Integrated ML-based signal generation with volatility-adjusted position sizing and risk constraints• Performed walk-forward validation and strict out-of-sample testing• Conducted realistic backtesting including transaction cost and slippage modeling• Evaluated performance using Alpha, Beta, Sharpe Ratio, Sortino Ratio, Maximum Drawdown, and Calmar Ratio via VectorBT Pro• Implemented dynamic risk management frameworks to control exposure and drawdownMachine Learning & Financial Modeling• LSTM-based time-series forecasting for financial markets• PPO-based reinforcement learning agents for adaptive trading systems• Advanced feature engineering including regime detection and volatility clustering• Automated ML pipelines reducing enterprise processing time from 286 days to 1 dayClient Impact• Delivered 20%+ revenue growth for 15+ e-commerce businesses• Improved campaign ROI by 25% using predictive allocation models• Built ML systems improving operational efficiency by 15–20%• Currently working with 3 long-term clients across quantitative research and applied MLI am open to selective contract engagements in: Quantitative Research Algorithmic Trading System Development AI in Finance Advanced Time-Series & Risk ModelingI focus on building systems that prioritize robustness, risk control, and measurable alpha not just model accuracy.

Experience

1. Quantitative Research & Financial Ml Consultant

   Independent

   Jul 2025 — Present · Gurugram, IN

   Serving as early-stage quantitative research partner to 3+ fintech and algorithmic trading startups• Designing and validating systematic equity & securities trading strategies using QuantConnect (Lean framework)• Establishing institutional-grade backtesting standards including transaction cost and slippage modeling• Implementing walk-forward validation and strict out-of-sample testing pipelines• Developing LSTM-based forecasting models and PPO-based reinforcement learning agents• Building foundational risk management systems including volatility-adjusted position sizing and exposure control• Evaluating performance using Alpha, Beta, Sharpe, Sortino, Maximum Drawdown, and Calmar Ratio (VectorBT Pro)• Achieved risk-adjusted Sharpe ratio of 1.3• Reduced drawdown by 30% using volatility-based allocation

Education

• Indian Institute of Technology, Indore

  Master of Science - MS, Data science and Management

• Thapar Institute of Engineering & Technology

  Bachelor of Computer Engineering

• Ys School

  12th, Non- Medical

• Indian Institute of Management, Indore

  Master's Degree

• Indian Institute of Management, Indore

  Master of Science - MS, Data Science and Management

• Thapar Institute of Engineering & Technology

  Bachelor of Engineering - BE, Computer Engineering