Currently pursuing an MSc in Mathematics & Finance at Imperial College London, building on my engineering background from Télécom Paris in Stochastic Modeling & Data Science. Focused on quantitative finance, systematic trading, and derivatives pricing.
Portfolio: paul-archer.vercel.app
- Multi-Asset Systematic Trading Framework: Built ensemble ML system combining XGBoost, LSTM, and Transformers on 250+ features, achieving 5.3% CAGR and Sharpe 1.34
- Quantitative Derivatives Engine: Implemented Black-Scholes, Heston, and Merton jump-diffusion models for exotic options with sub-200µs pricing
- VibeMatch: Co-founded AI-powered creator-sponsor matching platform using NLP for compatibility scoring
- Healthcare AI Research: Engineered NLP + OCR pipeline extracting structured data from unstructured physician notes at Henri Mondor Hospital, and developed research funding analyzer for academic publications; Top 10 finish at Google DeepMind Healthcare Hackathon with GEMCARE platform
- Alpha Contributor @ WorldQuant BRAIN Platform - Systematic signal research
- Research Intern @ Henri Mondor Hospital (AP-HP) - Time series forecasting and survival analysis
- Co-Founder & Technical Lead @ VibeMatch - AI marketplace platform
- Quantum Computing Intern @ Sopra Steria - Quantum optimization on Pasqal processors
- General Secretary @ Forum Télécom Paris - €300K budget management (Forbes feature)
Programming & Frameworks:
- Python (NumPy, Pandas, Scikit-Learn, PyTorch, QuantLib) ⭐️⭐️⭐️⭐️⭐️
- C++ ⭐️⭐️⭐️⭐️
- R ⭐️⭐️⭐️⭐️
- SQL, Excel VBA ⭐️⭐️⭐️
- Java, TypeScript ⭐️⭐️⭐️
Quantitative Methods:
- Stochastic Calculus: Itô's Lemma, Black-Scholes, Heston, Monte Carlo
- Time Series: ARIMA, GARCH, VAR, Kalman filtering, cointegration
- Risk Management: VaR, Expected Shortfall, Greeks calculation
- Machine Learning: XGBoost, LSTM, Transformers, NLP sentiment analysis
- Portfolio Theory: Mean-variance optimization, Kelly criterion, regime detection
- Quantitative Finance & Derivatives Pricing
- Systematic Trading & Statistical Arbitrage
- Machine Learning for Alpha Generation
- Stochastic Volatility & Jump-Diffusion Models
- Market Microstructure & High-Frequency Trading
Multi-Asset Systematic Trading Framework - Ensemble ML strategy with rigorous walk-forward validation
Quantitative Derivatives Engine - Black-Scholes extensions with exotic options pricing
VibeMatch - AI-powered creator-sponsor matching platform
GEMCARE - AI medical records platform (Google DeepMind Hackathon Top 10)
Research Funding Analyzer - NLP + OCR for academic publication analysis
Quantum Network Optimizer - Quantum algorithms for network optimization
- Optiver Ready Trader Go - High-frequency trading algorithms
- QuantConnect Alpha Competition - Systematic alpha generation
- Google DeepMind Healthcare Hackathon - Top 10 finish
French (Native) | English (C2) | German (B2)
- Email: paul.archer25@imperial.ac.uk
- LinkedIn: linkedin.com/in/p-archer
- Portfolio: paul-archer.vercel.app
- Location: London, UK
Applying mathematical rigor to quantitative finance challenges