Data Analyst — Product Analytics & Experimentation
Professional Summary
Data analyst with 4 years partnering with product and growth teams. I translate fuzzy product questions into testable hypotheses, ship the dashboards and experiments to answer them, and brief stakeholders on what the result actually means for next quarter's roadmap. Heavy on SQL + Python; comfortable owning the data model in dbt.
Technical Skills
- SQL (Postgres, BigQuery, Snowflake)
- Python (pandas, NumPy, scikit-learn)
- R
- dbt
- Looker / Tableau / Power BI / Metabase
- ETL / ELT pipelines
- A/B testing & statistical inference
- Cohort & funnel analysis
- Forecasting (ARIMA, Prophet)
- Git, Jupyter, dashboards (Streamlit)
Sample Experience Bullets
- Designed and ran 14 A/B tests on the signup funnel; the top 3 winners lifted week-1 retention by a combined 9.4 points.
- Built the company's first cohort-retention dashboard in Looker, replacing four conflicting hand-rolled spreadsheets; now the single source of truth for the weekly growth review.
- Owned the dbt model for billing events; cut nightly run time from 47 minutes to 11 by rewriting two CTE-heavy queries as incremental models with proper unique keys.
- Forecasted churn six weeks out with 87% MAPE accuracy using Prophet + a logistic-regression overlay on usage signals.