B.S. Information Sciences · Minors in CS, Health Technology & Cybersecurity · UIUC · 2026
Product manager and builder. I ship products, define the metrics, and engineer what needs to be engineered.
I sit at the intersection of product thinking and data engineering. I've launched AI features, built forecasting tools for Division I athletics, and delivered analytics systems for a Fortune 500 company. I own problems end-to-end.
Focus Areas
Data engineering & platforms
Ingest → model → serve. Contracts that don’t break, pipelines that self-heal, surfaces that drive action.
Health data & systems
Applied analytics for public health & care delivery: surveillance, forecasting, cohorting, and FHIR/HL7 mapping with privacy by design.
Cybersecurity by design
Security isn't a checklist. It's an architecture decision. Least-privilege IAM, auditable flows, explainable outputs, and secure defaults built into the product from day one.
Product mindset
I own the problem, not just the ticket. Discovery → metric → ship → iterate. I've written PRDs, run stakeholder reviews, and held the line on scope when it mattered.
Certifications
Projects
Financial Operations Forecasting
Built driver-based forecasting models and budget dashboards for a Division I athletics program. Unified historical actuals with forward-looking assumptions so leadership could scenario-plan in real time instead of waiting on static spreadsheets.
Postgame Survey NLP Pipeline
Automated the full lifecycle of postgame survey analysis: ingestion, cleaning, topic modeling, and sentiment scoring. Delivered tagged weekly summaries to leadership with zero manual effort. Raw athlete feedback became structured, actionable insight.
Operational Analytics Dashboards
Modeled KPIs end-to-end in dbt, wired them into a Power BI layer, and established a single source of truth across multiple data sources. Delivered dashboards that non-technical stakeholders actually adopted, not just opened once.
PhishNet AI: Phishing Detection
Built a phishing detection engine with risk scoring designed from the ground up for non-technical users. Explainability was baked in from day one. Every flag comes with a plain-language reason, not just a score.
Basketball Personnel Reporting Tool
Full-stack scouting and roster strategy dashboard covering NBA, WNBA, NCAAM, and NCAAW. Built a custom Player Impact Value (PIV) tier system, modeled NIL estimates for every college player from performance and conference data, and analyzed the pre/post-NIL era using a team-strength formula with recency decay. Four tabs: cap analysis, player development curves, full roster views, and an NCAA case study on how championship programs are built.
Consumer Product Industry Project
Delivered data workflows, product framing, and AI-powered search for a Fortune 500 company operating at scale. Built and integrated an AI search feature that let internal users query across company data conversationally. Details are under NDA. Happy to walk through the approach in an interview.
About
I’m a product manager and data engineer from the University of Illinois. I define what to build, ship it, and measure whether it worked. Most PMs hand off to engineering. I stay in the room because I can do the work.
I’ve shipped AI features for a Fortune 500 company, built financial forecasting tools for Division I athletics, and delivered analytics systems that non-technical leaders actually use. My background spans data engineering, health informatics, and cybersecurity — which means I ask better questions and catch problems earlier.
I believe the best products come from people who understand the data underneath them. That’s the edge I bring.
Beyond the work
Lifelong hooper and sports obsessive. The basketball tool exists because I actually care about the game, not just the data.
Certified personal trainer. Consistency is a system, not a mood. Same philosophy I bring to engineering.
I make content at the intersection of sports, tech, fashion, and hoops culture. Storytelling is a skill I use on both sides.
Gear head. I test gadgets and care deeply about the last 10% of the user experience, the part most people skip.