I'm a data scientist who started out in chemical engineering and materials science. I taught math and data science at Regis University in Denver for about 4.5 years, spearheading the Masters in Data Science program for 3.5 of those years.Currently I work with Empower, a fintech startup with a mission to bring fair credit access to all. I've been spearheading the machine learning systems for our flagship product, cash advance. This has required implementing the full gamut of collecting data and new features to use, training and optimizing models, deploying them to the cloud with serverless technology, maintenance and monitoring of models and data, and integrating the deployed models with our server-side code.Previously I worked at Tink, categorizing transactions for personal finance management and helping to create new engaging ML-enriched personal finance data for banks and consumers to use.On the categorization enrichment team, we used everyday transactions from bank accounts, and with machine learning magic we then assign a category for each transaction. This then feeds into your budgeting and other insights from your bank and finance apps. We used a host of tools including GCP, AWS, Python, SQL, Go, Java, and natural language processing (NLP) to clean up and categorize bank transactions. The ML systems are set up to automatically learn from customer recategorizations, and performance is automatically improving all the time. We processed billions of transactions.I have a broad range of interests and am interested in eventually working on some other projects if I can find the time, like AI/ML/NLP, food production, manufacturing, LED lighting, and other tech. The generic air gen effect is the project I would most like to work on next.