I received my PhD in Physics in 2021 and started working in the industry as a Data Scientist. My experience includes causal inference modeling, machine learning, R / python programming, version control systems, and working on pipelines to process clinical data and train models.
Built pipelines using R, Python, and DVC to process clinical genomic data, and build causal AI disease specific Digital Twins to increase software reusability
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Assembled Python packages to streamline the biological and literature search process to validate drug targets using
Git, GraphQL, requests, Beautiful Soup, unittest, and Pandas by processing thousands of genes automatically
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First authored abstract that validated 3 genes as causal predictors of survival in Multiple Myeloma patients using causal inference and survival analysis regression to reach company goal, and increase visibility at ASH conference
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Collaborated with multiple colleagues to standardize procedure to evaluate clinical data as part of stage 1 RnD and Precision Medicine collaborative process to take data from deliverable format to trained machine learning model
