Bio

I am an aspiring computational statistician.

My name is Ryan Tan (陈俊雄). I am currently pursuing a MSc in Statistics, following my graduation from the National University of Singapore with a BSc in Business Analytics with Honours. I am interested in the field of Sequential Inference which broadly covers State-Space Models, Monte-Carlo methods, and online Bayesian learning.

If my profile interests you, feel free to reach out to me on LinkedIn!

Education

• University of Warwick, MSc in Statistics (expected Distinction)(Expected Sep 2026) — United Kingdom
  • Relevant Courses: Statistical Learning, Bayesian Inference, Reinforcement Learning
• National University of Singapore - School of Computing, BSc in Business Analytics with Honours (Distinction)(May 2025) — Singapore
  • Relevant Courses: Data Structures and Algorithms, Computational Statistics, Machine Learning

Professional

• Bastion Trading · Proprietary Trading Firm, Quant Intern(Jul 2025 - Sep 2025) — Singapore
• Maven11 · Digital Asset Hedge Fund, Data Analyst Intern(Sep 2023 - Jul 2024) — Amsterdam, The Netherlands
• Stablecorp · Stablecoin Payment Infrastructure, Data Analyst Intern(Aug 2022 - Jul 2023) — Toronto, Canada
• Micron Technology · Semiconductor Manufacturing, Analyst Intern(May 2021 - Aug 2021) — Singapore
  • Part of Smart Manufacturing and AI group (SMAI).

Projects

• Risk Analysis of Leveraged Perpetual Futures using Monte Carlo Simulations(Jan 2025 - Mar 2025) — Fitted Pearson Type III distributions to BTC funding rates and returns and ran Monte Carlo simulations over 3-month horizons to estimate distribution of perpetual futures returns. Simulations projected 46% expected return with 0.85% liquidation risk at 2x portfolio leverage.
• Automotive Supply Chain Aggregator using LLMs(Aug 2024 - Dec 2024) — Partnered with Xeptagon to build an automotive supply-chain aggregator for structured extraction from company websites. Developed a RAG pipeline using Hugging Face embeddings for semantic matching. Implemented LLM-based structured extraction and benchmarked prompt strategies (zero-shot, one-shot, Chain-of-Thought) using hybrid similarity metrics, achieving 60% field-level accuracy.
• Market-Cap Weighted RSI Strategy(Aug 2024 - Dec 2024) — Developed a Python backtesting engine (vectorized and event-driven) to evaluate algorithmic strategies. Designed and validated a market-cap-weighted RSI mean-reversion strategy across 49 QQQ constituents. Implemented Efficient Frontier portfolio allocation using PyPortfolioOpt, achieving a 0.38 Sharpe versus the S&P 500 benchmark's 0.85.
• Lancer(Jan 2023 - June 2023) — A freelance aggregator platform to streamline freelance hiring process. Awarded $10,000 SGD from the NUS Venture Initiation Programme. Attended Collision 2023 under the Alpha Startup Programme.
• Sparklers(Jun 2023 - Jun 2023) — Web3 analytics dashboard to evaluate the credit of on-chain wallets. Won 1st Prize from Airstack and 3rd Prize from MakerDAO at ETHWaterloo 2023.
• Make Houston Rockets Great Again(Jan 2022 - May 2022) — Utilized NLP techniques to analyze Twitter and Reddit sentiment towards Houston Rockets and identified key factors using Latent Dirichlet Allocation (LDA) to provide recommendations for NBA team Houston Rockets.
• FitTogether(Jun 2021 - Jun 2021) — Participated in NUS Enterprise The Hangar Booster Programme. Pitched startup idea of FitTogether, a Flutter based fitness coach application.

Publications

• Dynamic Basis Arbitrage using Reinforcement Learning(2025) — Ryan Tan. Research on applying reinforcement learning to dynamically execute basis arbitrage.
• University of Warwick Statistics - Notes/Cheatsheets(2025/2026) — Ryan Tan. MSc Statistics. ST961, ST963, ST413, ST407, ST411, ST420, ST405, ST964.
• What Happens After the Hack? A Deep Dive Into DeFi Exploits and Recoveries(2023) — Stablecorp Team. Researched exploit risk across DeFi protocols and developed a proprietary risk score.