Paulina Zheng is a Senior Data Scientist in New York with eight years of experience building and deploying statistical and machine learning solutions across public health and biotech to customer engagement platforms. She combines a Columbia M.S. in Epidemiology and Applied Biostatistics and a strong back-end engineering skillset (Python, SQL, SAS) to translate complex biological and clinical data into production-ready models and features. Her work ranges from RNA-seq and protein-focused ML for drug discovery at Envisagenics to regression and policy-relevant analyses at NYC DOHMH, and she now drives data science at Braze. Known for bridging rigorous biostatistical thinking with pragmatic engineering, she often brings domain-aware feature engineering and reproducible pipelines to production ML.
8 years of coding experience
11 years of employment as a software developer
Master's Degree, Epidemiology, Applied Biostatistics, 4.0, Master's Degree, Epidemiology, Applied Biostatistics, 4.0 at Columbia University Mailman School of Public Health
Bachelor's Degree, Biology & Community Health, magna cum laude, Bachelor's Degree, Biology & Community Health, magna cum laude at Tufts University
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