Pratyush Upadhyay — Product Manager

📈 Quant & Algo Trader | MSc Financial Technology at Imperial College London | 6+ years of trading experience across asset classes I’m a quantitative developer and trader passionate about designing and deploying data-driven, statistically robust trading systems. With a strong foundation in financial econometrics, market microstructure, derivatives pricing, and systematic trading strategies, I bring both technical acumen and real-market intuition to the table. 🔧 Hands-on with real-time and live-deployed strategies: • Ultra-low latency arbitrage bot: Built for Indian equities (NSE-BSE); live deployed with a Sharpe ratio of 3+ • Crypto perpetual-forward arbitrage strategy: On-chain deployment using Kelly criterion for risk optimization • Dynamic cointegration pair trading: Kalman filter-based hedging with real-time tick data integration • Sentiment-based trading: Twitter NLP (VADER) + momentum overlays to trade FX and equities during macro shifts 💻 Technical stack: Python (Pandas, NumPy, statsmodels, scikit-learn), C++, SQL, Java, Bloomberg, Spring Boot, NLP, Azure 🏆 Achievements: • Winner, Bloomberg Trading Challenge @Imperial (Top 10% globally) • Featured on India’s leading finance podcasts for insights on derivatives and systematic strategies • Research indexed on Google Scholar | Published deep learning framework for accessibility 👨‍💻 Previously worked at Tata Consultancy Services as a full-stack developer building scalable FinTech solutions. 🔍 Actively seeking: Quantitative research, systematic trading, or algo strategy roles — where I can contribute to signal discovery, alpha generation, or model implementation in live markets. Let’s connect if you’re hiring for quant/algo roles or want to talk about market inefficiencies, strategy back testing, or low-latency execution and programming.

Stackforce AI infers this person is a Fintech professional with expertise in quantitative trading and algorithm development.

Location: London, England, United Kingdom

Experience: 3 yrs 3 mos