I’m Matt Goh — a data scientist with a background that spans the energy sector, agricultural biotech, and academic neuroscience research.
What I do
I work at the intersection of machine learning, statistics, and domain science. I’m comfortable across the full data pipeline: from exploratory analysis and feature engineering, to building and deploying models, to designing the infrastructure that makes it all reproducible.
Where I’ve worked
SoCalGas (current) — Applying data science to problems in the energy sector.
Trace Genomics — An agricultural biotech startup. We combined genomics, soil chemistry, and machine learning to give farmers a window into their soil microbiome and help them make smarter agronomic decisions.
Brain Imaging Research — Spent several years as a researcher studying neurodegenerative diseases using neuroimaging data. This meant applying statistics and ML to MRI and DTI datasets, as well as building the data processing pipelines (preprocessing, registration, QC) that made large-scale analysis feasible.
Interests
- Machine learning and predictive modeling
- Computational biology and genomics
- Neuroimaging and brain connectivity
- Building data pipelines and tooling that makes research reproducible
Get in touch
The best way to reach me is via GitHub. You can also find my publications and CV linked in the nav.