Career
Quant developer and data engineer. MSc Computational Finance at King's College London (2026), BSc Computer Science at Nottingham. Recently a Data Engineer at Blockchain.com — ETL and CDC pipelines into BigQuery, Terraform, CI.
Projects
CLMM-Bench: out-of-sample audit of Uniswap v3 LP strategies
MSc thesis. A reproducible backtesting framework over five Uniswap v3 pools showing that walk-forward-selected liquidity-provision configurations don't beat a never-rebalanced position — and that overfitting diagnostics change sign with transaction costs.
Agent-based prediction-market simulation of the BTC spot market
Discrete-time agent-based model of heterogeneous BTC traders reacting to Polymarket belief signals. Stronger herding pushes order imbalance to extremes and flips price dynamics from noisy to persistent one-sided regimes.
StockMARL: multi-agent reinforcement learning for trading
Published BSc research. A multi-agent RL trading system with a DQN agent learning alongside diverse rule-based agents — 12.23% money-weighted annual return and 15.9% cumulative return on unseen S&P 500 data with low trade volatility.
Deep learning for financial time-series forecasting
Mentor-led research with Prof. Antoine Jacquier (Imperial). LSTM models forecasting daily US-equity returns; owned the pipeline end to end from data cleaning and feature construction through walk-forward evaluation.
Credit scoring system
End-to-end credit-evaluation model built at Capgemini (Shenzhen): preprocessing, binning, feature selection, training and testing — 81% classification accuracy.
Writing (technical)
Coming — notes on markets, on-chain data, and the tools I use.