I am a business academic and data scientist with expertise at the intersection of applied statistics, machine learning, product and growth. I enjoy implementing a broad array of analytical tools to scale expansion in high growth environments.For more on my research or other activities, please visit www.isaacdinner.comAssorted research interests, methods and tools:time series, forecasting, marketing mix modeling, advertising effectiveness and measurement, data privacy, clean rooms, attribution modeling, large-scale field experiments, A/B testing, applied econometrics, causal inference, causal machine learning, lasso, ridge, clustering, bayesian statistics, behavioral economics, two-side markets, multi-sided markets, discrete-choice modeling, predictive modeling, business intelligence, analytics, customer lifetime value, pricing. R, SQL, Python, Stata, SAS, snowflake, airflow.