Transforming product strategy through data science. 7+ years in tech PM/Marketing, now specializing in machine learning and AI-driven solutions that deliver measurable business impact.
Bridging business strategy and technical execution through data-driven insights
Showcasing the intersection of data science and product strategy
Processed 4.7M+ arrest records from NYPD/LAPD datasets with advanced statistical analysis, temporal pattern recognition, and geospatial density mapping to identify population-crime correlations. Developed automated analytics pipeline delivering stakeholder-ready insights for urban planning and resource allocation through data standardization and visualization techniques.
View Case StudyEngineered automated financial data pipeline integrating EODHD API to analyze $1.2T+ S&P 500 ETF performance, calculating risk-adjusted returns and revealing 8.5% performance differential between weighting strategies. Applied quantitative analytics methods with real-time processing of 231 trading days, volatility modeling, and portfolio optimization insights for institutional investment decisions.
View Case StudyBuilt production-ready ML pipeline processing 300K+ NBA game records with automated web scraping, K-means clustering, and PCA analysis to identify team performance patterns and championship-winning strategies. Implemented scalable data engineering system with checkpoint recovery, statistical validation, and automated feature engineering for multi-dimensional sports analytics.
View Case StudyBridging business strategy and technical execution through data-driven insights.
I transform complex business challenges into actionable insights through machine learning and data science, bringing a unique perspective from 7+ years in product management and marketing. My background in product development allows me to understand both business objectives and user needs, ensuring that every data-driven solution I create delivers measurable business impact rather than just technical achievements.
I specialize in building ML models that solve real problems while remaining interpretable and scalable for production environments, always keeping the end user and business goals at the forefront.
Interested in working together? Have a project in mind? I'd love to hear from you.