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My passion is using data to solve problems. I like building robust and scalable end-to-end solutions with great documentation. Trained in analytics with a background in quantitative research and university teaching, I have 10+ years of experience drawing insights from data and communicating results in digestible ways. Analytical skills • Applied use cases: Behavioral segmentation, A/B testing, anomaly detection, churn prediction, customer health scoring, time-to-value estimation, user journey analyses • Statistical techniques: Generalized linear and additive models, multilevel modeling, factor analysis, structural equation modeling, experimental design, bootstrapping, Monte Carlo methods • Machine learning techniques: Supervised learning, clustering, multi-armed bandit algorithms, Bayesian optimization Technical tools • Modeling: SQL, Git, dbt, Jinja • Analysis: Python (sklearn, xgboost, pandas, seaborn, scipy), R (dplyr, ggplot2, lavaan) • Visualization: Tableau, plotly Dash, Sisense/Periscope, Redash, Apache Superset • Warehousing: BigQuery, Snowflake, PostgreSQL • Tracking: Snowplow, Segment • Integration: Fivetran, Hightouch, Census • Notebooks: JupyterLab, Deepnote, Hex, Colaboratory
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