I'm Chris Shymansky, an experienced data scientist, chemical engineering Ph.D, and wannabe chef.
I'm a data vanguard. I assess datasets, clean them, identify ways to extract value, and execute on the most impactful projects that generate the most excitement from stakeholders. Oftentimes this means building APIs powered by data and deep/machine learning. Sometimes this means identifying actionable insights to inform decisions or optimize the work of other teams. Additionally, I automate team workflows, build ETL systems and custom metrics, and implement algorithms from the scientific literature.
I received my Ph.D in chemical engineering from the University of California, Berkeley. There I genetically engineered baker's yeast to produce biofuel, fed these strains 13C-labeled sugar, and used the resulting data with network flow models to identify genetic interventions to redirect the flow of material to fermented products. I munged messy data, used SQL to store/maintain/query it, used scikit-learn for machine learning, and used Python/numpy to optimize convex optimization algorithms. This, naturally, led me to Data Science!
In my free time I enjoy trying out and optimizing recipes, exploring Oakland and Berkeley, playing mostly single player games (e.g. Elden Ring, Deathloop, etc.), watching various shows (e.g. RuPaul's Drag Race, Game of Thrones, What We Do in the Shadows, etc.), reading Hacker News discussions, reading a LOT of Medium articles, and tinkering on projects involving data, its modeling/visualization/limits, web development, Bayesian statistics, and functional programming, among others.