Matthew Peters is a Senior Data Scientist and biostatistician with 13 years' experience applying statistical rigor and machine learning across healthcare, insurance and finance. Holding a Masters in Medical Statistics, he blends Bayesian and mixed-effects modeling with practical supervised and unsupervised ML to turn longitudinal and real-world clinical data into policy- and product-facing insights. He has led high-impact projects—from designing synthetic controls to evaluate opioid interventions to developing customer segmentation and pricing models that materially improved marketing outcomes and claims pricing. Deep database and engineering experience (SQL, Postgres, MongoDB, VB.NET, Python, R, SAS) lets him own pipelines end-to-end and deliver reproducible analyses at scale. Prince2 and ICH-GCP certified, he pairs technical depth with structured project leadership and a consistent track record of translating complex data into actionable decisions. An analytical polymath, he often combines unconventional methods (novel validation formulas, calculus-based filters) with classical statistics to solve messy real-world problems.
12 years of coding experience
13 years of employment as a software developer
Diploma of Information Technology(database design and development), Information Technology, Diploma of Information Technology(database design and development), Information Technology at The Northern Sydney Institute - TAFE NSW
Masters in medical statistics, Statistics, GPA 5.8/7 ~83%, Masters in medical statistics, Statistics, GPA 5.8/7 ~83% at University of Newcastle
Graduate Certificate in Applied Statistics, Statistics, GPA: 5.5/7 ~79%, Graduate Certificate in Applied Statistics, Statistics, GPA: 5.5/7 ~79% at Charles Sturt University
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