Summary
Matthew Walker is a Senior Data Scientist based in Wellington with 13 years of experience applying machine learning and software engineering to real-world problems across industry, defence, and healthcare. He holds a PhD in Genetic Programming and a postdoc in multi-objective optimisation, and has turned those research skills into production systems—from deep-learning vision on Raspberry Pi to cloud-hosted audio conferencing and automated building-energy fault detection. He has led teams (up to seven) to deliver complex products such as a stochastic weather generator for probabilistic risk analysis and has strong hands-on expertise across Python, R, Java/C/C++, SQL, and domain-specific tools like SkySpark. His consulting work blends statistical rigour and practical engineering: examples include Monte-Carlo financial modelling, a 27-year dermatology study re-analysis, and verifying large multi-spreadsheet economic models. He contributes to open-source tooling (notably refining a Python .msg extractor) and is comfortable owning projects end-to-end—from pitching multi-hundred-thousand-dollar programs to commissioning and support. A polyglot coder who enjoys language learning, he combines academic depth with a pragmatic focus on deployable, auditable solutions.
13 years of coding experience
3 years of employment as a software developer
Post-doc, Evolutionary computation applied to Wireless Sensor Networks (WSNs), Post-doc, Evolutionary computation applied to Wireless Sensor Networks (WSNs) at Université Laval
Kristin School
Doctor of Philosophy (Ph.D.), Machine Learning, Doctor of Philosophy (Ph.D.), Machine Learning at Massey University
English, French