B.S. Information Sciences · Minors in CS, Health Technology & Cybersecurity · UIUC · 2026
I build data systems and the products they power.
Pipelines, models, and the dashboards people actually make decisions with. Currently building data infrastructure inside a Division I athletics operation: automated ingestion across REST API and FTP sources, and the reporting leadership runs on. I've also launched AI features and delivered analytics systems for a Fortune 500 client. 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
Automated Data Pipeline (Sports Analytics Integration)
Built automated Python pipelines that replaced a manual multi-step download process, extracting six data types from a third-party sports analytics platform across both REST API and FTP channels. Integrated the REST API via OAuth 2.0 and parsed 2,400+ session records into pandas DataFrames. Engineered an FTP workflow that filtered a national data-sharing network from ~11,000 files (2.8 GB) down to 110 relevant files (23 MB), cutting extraction time with MLSD batch listing. Secured all credentials and private athlete data with environment variables and gitignore policies.
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.
NASA Space Apps Challenge: The Urban Planning Initiative
Designed the backend architecture for a tool helping Chicago city planners identify environmental and socioeconomic patterns. Built API endpoints, data processing pipelines, and AI-powered insight modules supporting real-time analysis of population density, air quality, income, and weather data. Integrated geospatial and statistical datasets from multiple sources, delivered under hackathon time constraints on a multidisciplinary team.
PhishNet AI: Phishing Detection
Paste a suspicious message and get a risk score with the specific signals behind it. Rebuilt after finding that v1 parsed model output with a regex and left the score at its default of zero whenever that regex missed, rendering dangerous messages as a reassuring green. v2 constrains the model to a JSON schema, throws instead of defaulting, and recomputes the risk level from the score rather than trusting the model to keep them consistent. The API key now lives in a serverless function, after I found it hardcoded in the v1 frontend on a public repo. Also includes a password generator built to NIST SP 800-63B: entropy computed from the real wordlist, no forced composition rules.
Basketball Personnel Reporting Tool
Full-stack scouting and roster strategy dashboard across four leagues (NBA, WNBA, NCAA M/W). Designed a team-strength model with era-adjusted weights (pre/post-NIL) and exponential recency decay to rank top programs over a 10-year window, plus an NIL valuation model estimating compensation for 1,000+ college players from performance metrics, conference strength, and playing time. Interactive Recharts visualizations analyze pre vs. post-NIL roster trends, with raw CSV data transformed at build time via PapaParse.
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.