Applied Scientist, Marketing Measurement

Applied Scientist, Marketing Measurement Department: Data Science Team: Data Scientist Location: New York, United States Type: Full-Time **About the Role** As an Applied Scientist on the incrementality foundations team within marketing measurement, you will contribute to Uber Marketing Org’s commitment to science-backed decision making. This team is responsible for building experiment forms, models, & processes for turning complex hypotheses into reliable, actionable incrementality signals that inform planning, forecasting, and investment decisions across the business. Your work will focus on building robust processes for interpreting measurement data, building foundational models for estimation & inference, and researching experimentation best practices for accurate and complete incrementality measurement. Your work will inform smarter investment and decision-making systems across Uber's Brand and Performance Marketing. This team sits close to production systems, partnering with Product, Engineering, and cross-functional Science teams to ensure incrementality measurement is rigorous, scalable, and decision-ready **What the Candidate Will Need / Bonus Points** - Develop and apply statistical and causal inference models to estimate the incremental impact of marketing across channels, markets, and test designs. - Design custom tests & analyze results from complex experiments, including multi-cell, market-level, and longitudinal tests. - Contribute to foundational modeling efforts such as hierarchical smoothing, aggregation across tests, and handling of low-signal or sparse data. - Assist in research on advanced topics, including learning elasticity with experiments and analyzing event relationships to improve experiment accuracy and interpretation. - Partner with Product and Engineering to integrate incrementality models into reporting and decision-making workflows - Research and help establish best practices for experiment design, post-analysis interpretation, and measurement tradeoffs. - Collaborate with other Applied Science and Data Science teams to align incrementality outputs with broader meas