Data · Technology · Communication
I build data-driven products, solve technical complexity, and translate both into clear user value and business strategy.
I am a Product Manager with the technical foundation of a computer scientist and the analytical lens of a data scientist. My transition into product was born from a fundamental realization: analyzing data is entirely different from understanding which data actually matters to a product's survival. Because I know how engineering architectures are built, I don't manage by guesswork or pass off vague requests to developers. Instead, I step into ambiguous spaces to untangle product tracking, rewrite technical requirements with absolute clarity, and move teams away from vanity dashboard numbers toward the core behaviors that make a product sticky.
Outside technical work, I write. My Medium blog explores product thinking, technology decisions, and honest reflections on being in transition — because explaining complexity clearly is a skill I take as seriously as building things.
"I don't just run the analysis — I can tell you what it means, and what to do next."
"A very cleanly written report. Much of it wouldn't be out of place in a computer science journal article. The XAI analysis is particularly impressive — the level of reporting, in terms of both the way data is presented and the depth of analysis, is what I'd expect to see in a journal article."
Next-day PM2.5 forecasting across three under-monitored cities using only open data — satellite night-time lights, meteorological reanalysis, and ground sensors. Compared XGBoost against deep learning sequence models. Applied SHAP explainability to translate complex model outputs into an intuitive, high-utility interface for urban health decision-makers, minimizing cognitive friction.
Geocoded 4,325 polling units, manually corrected 17 erroneous location entries, and applied geospatial neighbourhood analysis to compute voting outlier scores for each party. Built interactive maps showing the top 3 anomalous units per party — making statistical findings navigable without reading a report.
Group project classifying human vs. natural wildfire causes across a 28-year US dataset. Benchmarked seven algorithms — including CatBoost, CNN, MLP, and Decision Trees — with and without SMOTE for class imbalance. Acted as cross-functional product owner and documentation lead for a 4-person team; managed project scope under tight deadlines and translated raw model performance metrics into an executive-ready technical report. Implemented K-Means clustering and contributed collaboratively to model development.
Investigated the emerging tension between aggressive corporate monetization and direct consumer trust within the world's leading digital women's health platform. To bypass superficial metric tracking, compiled a custom dataset of 1,442 platform reviews across the iOS and Android application stores and built a BART-Large-MNLI Zero-Shot NLP Classifier to programmatically isolate systemic churn vectors.
Explored the structural gap between data exploration and strategic product decision-making, drawing on my transition from data science to product management to outline a value-first framework for metrics. Using a household management application as a core case study, the analysis breaks down how early-stage product teams routinely fall into the trap of measuring default, countable output metrics—such as raw sign-ups or generic session clicks—instead of tracking true user value
I am looking to join product organizations where deep technical range is leveraged to drive real strategy and user value. If you are looking for a Product Manager who can write code, talk data, and ruthlessly prioritize for impact, let’s talk. drop me an email or reach out on LinkedIn.
