$0Documented Business Value$10M (Freenome) + $7M (Change) + $3M (Shipt)
0Models TrainedAutoTrader alone
0Max GMV LiftShipt A/B-tested shelves
0Scientists SupportedFreenome ML platform
0Engineered FeaturesAutoTrader feature store
0Berkeley DegreesCS + Data Science
What I Talk About Most
Keywords extracted from my resume, portfolio, and project documentation. Sized by frequency. Hover for context.
Primary language across every rolePythonTitle, identity, and passionMachine LearningCurrent focus at ShiptPersonalizationShipt two-tower + AutoTrader featuresEmbeddingsShipt + AutoTrader + FreenomeFeature EngineeringBuilt infrastructure at every companyInfrastructureCore at Shipt, Riviera, AutoTraderRecommendationsFreenome + AutoTrader + Shipt GCSGCPUsed at AutoTrader, Shipt, Riviera, CastlightXGBoostFreenome platform + Shipt experimentsA/B TestingUsed across every roleSQLApproximate nearest neighbors at scaleFAISSFreenome deep learning adoptionPyTorchShipt two-tower recommenderTwo-TowerCore ML task across careerClassificationAutoTrader + Shipt + FreenomePostgreSQLSentic package + Doximity + AutoTraderNLPShipt real-time recommendation deliveryKafkaRiviera, Castlight, Change, AutoTraderRegressionFreenome experiment trackingMLFlowTaught 50+ people at FreenomeGitFreenome + Shipt orchestrationAirflowFreenome core productCancer DetectionAlways ships to productionProduction SystemsFreenome + AutoTraderDeep LearningShipt GMV, engagement, NDCGMetrics DesignShipt RAG + agentic frameworkRAGRiviera + Shipt shelf rankingRanking ModelsAutoTrader hyperparameter searchOptunaShipt data warehouseSnowflakeFreenome ML executionFlyteChange Healthcare cloud toolsAWSFreenome containerizationDockerFreenome orchestrationKubernetesShipt Interaction ScoreComposite ScoringShipt + Freenome establishedCI/CDEEG research at BerkeleyBrain-Computer InterfaceSentic package, 20+ languagesSentiment AnalysisAutoTrader walk-forward validationTime SeriesFreenome petabyte-scale genomicsGenomicsAutoTrader VWAP labelsVWAP
A Few More Charts
Skills Depth
Self-assessed relative proficiency across disciplines
Time Across Domains
Approximate years spent in each industry
Top Keywords by Frequency
How often key terms appear across my resume, self-evaluation, and project docs
Technology Timeline
When I picked up key technologies and how long I've used them professionally
20152016201720182019202020212022202320242025
Things That Don't Fit on a Resume
The Running Club
I built an ML model to predict depression from lifestyle data. Its feature importances showed me that exercise and social activity mattered more than I thought. I joined a running club the next week and haven't stopped.
$55/Month
AutoTrader trains 1,800+ models, generates predictions for 600+ tickers, and delivers subscriber emails every morning—all on two GCP VMs that cost less than a gym membership.
The Git Teacher
At Freenome I taught git to over 50 scientists and researchers through an internal instructional series. Turns out the hardest part isn't rebasing—it's convincing a PhD that version control is not optional.
16 Repositories, 1 Person
When Shipt's Personalization team was first formed, I was the only data scientist for four months. Maintained all 16 Discovery Science repositories solo while simultaneously designing the next generation of infrastructure.
The Honest Metric
At Shipt, I discovered that the team's flagship KR (5% GMV attribution) couldn't be reproduced. Instead of quietly working around it, I documented the discrepancy and presented the real number (1–4%). It led to better metrics for everyone.
XRP to S&P 500
My first algorithmic trading project was a Ripple (XRP) sentiment bot in 2014 that won 3rd place in a Ripple API contest. A decade later, I'm running 1,800+ models across the S&P 500. The itch never went away.