Mason Veilleux
Building Machine Learning and AI pipelines
I design and build machine learning and AI pipelines for optimizing decisions under uncertainty. I care most about ones that are transparent, trustworthy, and give decision-makers the confidence they need.
I am most excited about building and deploying statistical models to optimize decision-making alongside fostering a culture of trust and empowerment with data.
Selected work
Ohio, United States · Remote
San Francisco Bay Area · Remote
Anchorage, Alaska, United States
Anchorage, Alaska, United States
Kent, England, United Kingdom
Recent projects
Bayesian team-strength estimation for sports analytics. Recovers latent offense and defense parameters by season-week and returns posterior predictive distributions for game outcomes.
Combines auction theory with Bayesian decision science so construction estimators can price bids at the profit-maximizing level in minutes rather than days.
Things that inspire me
- —Observational Price Variation in Scanner Data Does Not Reproduce Experimental Price Elasticities
Observational causal inference falls short of experimentation — this is why you need experimentation.
- —The Soul of Erlang and Elixir
Perfectly captures how resilient systems interface with a functional language.
- —You Can Just Do Things
The ending of a Neovim tutorial that hooked me into making Neovim my daily driver. You get to decide how your daily software tools look, you can have fun building them, and you can make them work best for you. I try to instill this mantra daily.
Recent writing
You can find more in my projects and occasional writings. I can be reached at masonjveilleux@gmail.com.