Parul Laul is a data scientist in the New York City area with a decade of experience translating complex data into actionable insights across healthcare and consumer wellness. She currently applies statistical modeling and production ML at WW, and previously developed unsupervised hospital-benchmarking models, patient risk predictors, and robust ETL pipelines at Vituity. Parul’s background includes a PhD in mathematics and postdoctoral research in general relativity, which informs her rigorous approach to modeling, algorithm design, and feature engineering. She also has teaching and curriculum development experience from several universities, having overseen undergraduate research and co-authored calculus workbooks. Comfortable moving projects from research to production, she combines strong theoretical foundations with practical data engineering and domain-savvy solutions.
10 years of coding experience
6 years of employment as a software developer
Data Science, Data Science at The Data Incubator
Master’s Degree, Mathematics, Master’s Degree, Mathematics at University of Toronto
Doctor of Philosophy (Ph.D.), Mathematics, Doctor of Philosophy (Ph.D.), Mathematics at University of North Carolina at Chapel Hill
Contributions:3 PRs, 198 pushes, 2 branches in 3 years 6 months
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