Erin Gill is a bioinformatics-focused data scientist and university research associate with 11 years of experience applying machine learning, statistical genomics, and cloud-backed data engineering to infectious disease research. Based at Simon Fraser University and active in CoVaRR-Net’s CAMEO initiative, she has built ETL pipelines, deployed PostgreSQL on AWS RDS, and produced interactive web tools (Flask and Shiny) that translated SARS-CoV-2 sequencing and vaccine eligibility data into actionable insights for public health. Her work spans hands-on algorithm development—novel R statistical methods and Python ML packages for outlier detection and forecasting—to program management and cross-disciplinary coordination that guided national-level briefings. Unusually for an academic, she blends production-grade web/apps and database deployments with deep genomics expertise from a PhD in Genetics, enabling both rapid prototyping and policy-facing delivery.
10 years of coding experience
11 years of employment as a software developer
BSc Biochemistry and Biology (honors), BSc Biochemistry and Biology (honors) at Dalhousie University
PhD Genetics, PhD Genetics at The University of British Columbia
Methods to automatically parse longitudinal numeric data for outliers using IQR and modified z-score, will also predict future time points using linear regression
Contributions:6 PRs, 15 pushes, 1 branch in 2 years 1 month
A simple GUI that allows users to check whether mutations from a SARS-CoV-2 genome best fit a mutational distribution of genomes derived from global, chronic, or deer infections.
Contributions:14 PRs, 118 pushes, 6 branches in 8 months
mutation-analysissars-cov-2zoonoses
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Erin Gill - University Research Associate (Junior Faculty)