Data science and AI executive. Thirteen years building analytics organizations, data platforms, and production AI products, most of it in healthcare.
Started as an analyst in 2013. Medicare claims research, clinical trials, behavioral health, value-based care economics, and the leadership roles on top of them.
A healthcare SaaS company's book of business renewed at 97% in a year. Behind that number: the customer health scoring engine Tyler built, which told success teams which clients needed attention and when.
HIPAA-governed CMS and Medicare claims, FDA submissions at a medical device company, FERPA-compliant architecture as a startup co-founder.
Conceived, designed, and shipped end to end: autonomous research agents, automated QA systems, retrieval-grounded assistants, consumer-facing tools.
JAMA Network Open, JAGS, BMJ Open, Scientific Reports and more, plus five peer-reviewed conference abstracts. Full list below.
Modern stacks (Snowflake, dbt, Fivetran, semantic layers, AI-powered self-service analytics) stood up from nothing at two different companies.
Tyler started in supply chain and logistics, moved into clinical statistics at a medical device company, programming datasets for FDA submissions, and then spent a decade in healthcare research and data science leadership. His Medicare claims work supported analyses behind federal drug-price negotiation policy and the Independence at Home Act of 2017.
As a director he has built data organizations and platforms end to end, twice from zero: modern warehousing and semantic layers, AI-powered self-service analytics, and a research institute publishing from proprietary care-coordination data. Alongside the leadership work, he designs and builds production AI products himself: autonomous research agents, automated quality-assurance systems, and retrieval-grounded assistants.
He holds dual business degrees from Arizona State's W. P. Carey School of Business, including supply chain management, which is why his approach to operations problems starts with constraints and flow rather than software features. Kent Applied is the practice he built to do this work directly for organizations that need it.
Peer-reviewed research, with the venues that reviewed it.
Tell Tyler what you're up against. Twenty minutes gets you a straight answer on whether it's an AI problem, a data problem, or neither.
Or connect on LinkedIn.