Principal Data Scientist with expertise in economic modeling, Bayesian, and genomics/bioinformatics

Ex-Microsoft L66 Principal Data Scientist, UW Statistics PhD, Caltech undergrad, fmr CFA. Can work as IC or hands-on lead, lot of experience ramping up junior DS IC's, whether from technical or MBA-type backgrounds. Mainstream work: economic modeling, causal techniques, financial risk, forecasting, unit economics/pricing/incentives, metric design, and experimentation. Recently I've been working on crowdsourcing/human relevance/RLHF; if you're using humans to generate training or optimization data, talk to me about designing incentives and monitoring quality. Special interests: all things Bayesian, uncertainty quantification, genomics/bioinformatics. Also consider hiring me to advise/consult on 1) building up your data science team, 2) choosing a data science architecture, 3) untangling and simplifying a messy data science infrastructure, 4) due diligence/BS detection when dealing with counterparties in the data science space.