Sr. Data Scientist

ABOUT THE ROLE We are looking for a Senior Data Scientist specializing in Marketing Mix Modeling (MMM) to help build and scale our in-house global marketing measurement capability. This role will own the development, validation, and evolution of statistical models that measure the incremental impact of marketing investment across channels, funnel stages, products, markets, and business outcomes. The ideal candidate combines deep hands-on MMM experience, strong statistical programming skills, and strong business storytelling capabilities. This person should be equally comfortable working directly with model code and translating complex analytical outputs into actionable recommendations for Marketing, Media, Finance, and executive leadership. The Senior Data Scientist will have a strong understanding of MMM methodology and be comfortable working across multiple modeling approaches, including custom-built Bayesian models and established MMM frameworks. They should be able to understand underlying code, evaluate alternative methodologies, diagnose model behavior, and adapt or extend the modeling approach as business and measurement needs evolve. Beyond core MMM development, this person will help build response and saturation curves, marketing budget optimization and scenario-planning capabilities, and models measuring marketing's impact on intermediate outcomes such as brand health and organic traffic. The successful candidate will help establish MMM as a scalable internal global decision-making capability that enables the business to understand what marketing and media drove, why performance changed, and where to invest next. They will build robust measurement of incremental marketing contribution across channels, products, markets, and the customer funnel; connect model results with changes in investment, media strategy, buying behavior, audience strategy, and market conditions; and translate MMM into response curves, marginal effectiveness, scenario planning, and optimization capabilities that inform future marketing investment decisions. Success means building a capability that is statistically credible, technically scalable, and actionable enough to influence real marketing and financial decisions. YOUR DAILY IMPACT AT PELOTON Develop, maintain, and enhance global Marketing Mix Models measuring incremental marketing impact across channels, products, markets, and business outcomes Work directly with underlying modeling code to diagnose, modify, and extend the modeling framework Evaluate alternative model specifications, methodologies, transformations, interactions, and assumptions based on statistical performance and business context Develop and evaluate appropriate adstock and carryover transformations, recognizing differences in how brand/upper-funnel, consideration/traffic-driving, and performance/lower-funnel media influence consumer behavior Identify and incorporate appropriate baseline and control variables, including seasonality, promotions, pricing, product availability, macroeconomic and industry factors, organic demand, and other relevant business drivers Diagnose model fit, stability, contribution estimates, incrementality, and potential issues including multicollinearity, confounding, cannibalization, or implausible model behavior Develop robust validation approaches using holdouts, out-of-sample performance, experiments, and other available sources of incrementality evidence Develop models measuring media's impact on intermediate outcomes, including brand metrics and organic/direct traffic Identify and evaluate new variables and hypotheses that improve our understanding of how marketing influences consumer behavior Connect upper-, mid-, and lower-funnel measurement and account for differences between short-term response and longer-term marketing impact Develop channel-level response and saturation curves to quantify diminishing marginal returns to marketing investment Tra