Ridham

Quantitative data scientist at an options trading firm. I backtest options strategies across NSE, BSE, MCX and US markets and built the Python / Polars / DuckDB pipeline behind the research — 1B+ rows, load times cut from hours to seconds

Jr. Data Scientist at Pranjali Grow Cap Pvt Ltd (2025-09 – Present)

• Identified the firm's top-performing options setups — measured by backtested PnL across days-to-expiry, weekday and strike — by designing and testing quantitative trading strategies for NSE, BSE, MCX and US derivatives markets.
• Cut strategy research turnaround from hours to seconds on 100M–1B+ row options datasets by replacing full Excel reloads with an incremental Python + Polars pipeline that re-processes only new market data.
• Enabled near real-time strategy analysis for the trading team — dashboards refresh in seconds instead of hours — by building a DuckDB-over-Parquet query layer and a Streamlit app with an Excel-style drag-and-drop pivot builder and automated Excel heatmap generation (xlwings).
• Optimized strategy selection across thousands of parameter combinations per backtest — evaluating profit potential and risk exposure of each variant under diverse market conditions — via a systematic PnL aggregation framework that separates robust setups from noise.
• Automated daily data updates, eliminating manual reloads entirely, by engineering memory-optimized ingestion (RAR → Parquet, chunked aggregation) that processes millions of rows per run within tight memory limits.

Bachelor of Computer Applications in Computer Applications – Guru Gobind Singh Indraprastha University (2022 – 2025)