At Behamics, I analyze large-scale e-commerce behavioral and transactional data to evaluate customer journeys, experiments, and business metrics including conversion rate, AOV, RPV, and uplift.
I run A/B tests and nudge-effectiveness analyses using confidence intervals and statistical significance testing, while investigating unexpected revenue and conversion changes.
Previously at Attributy, I improved a production multi-touch attribution pipeline through more reliable ingestion workflows, third-party API integrations, and analytics-ready PostgreSQL tables. I also reduced latency in SQL and agentic AI analytics workflows through refactoring, pre-aggregation, caching, connection pooling, and batched metric queries.
I've also built ETL pipelines, star-schema data warehouses, Spark and MongoDB workflows for multi-million-row datasets, and analytical dashboards in Power BI and Looker Studio.
