Summary
James Mcguigan is a versatile data scientist and seasoned full‑stack engineer with 11+ years of experience delivering production search, ML and data engineering solutions across enterprises like Credit Suisse, NASA and Rolls‑Royce. A self-taught Kaggle Expert and prolific GitHub portfolio owner, he builds creative ML systems (CNNs in TensorFlow/PyTorch, multilingual sentence embedding search, Prolog-style SAT solvers) and performance‑tuned algorithms (vectorised bitshifting, ant colony optimisation, geometrically invariant hashing). He’s repeatedly rescued and upgraded ElasticSearch deployments at scale—optimising analyzers, queries and pipelines—for high‑traffic services such as NHS Jobs and Condé Nast. Comfortable from low‑level algorithm design to DevOps and visualization, he’s fluent in Python, JavaScript, Bash and ElasticSearch, and is actively exploring Rust and WASM. His background as a CAD draftsman and formal science education give him an unusual aptitude for precise abstractions and engineered, testable solutions.
11 years of coding experience
11 years of employment as a software developer
BSc (Honours), Information Technology and Computing (2:1), BSc (Honours), Information Technology and Computing (2:1) at The Open University
Natural Science Tripos, Natural Science Tripos at Cambridge University