Applied Scientist II

Uber
New York, United StatesPosted 5 March 2026

Job Description

Applied Scientist II Department: Data Science Team: Data Scientist Location: New York, United States Type: Full-Time **About the role** We’re looking for an Applied Scientist to join our Brand Science team to provide strategic, actionable insights around how to measure and optimize a large brand marketing budget. In the role, you’ll be part of and collaborate with a cross-functional team consisting of marketing/media stakeholders, our in-house research and insights team, as well as other scientists across the broader organization. Problems we’re working on include: - How do we measure the impact of advertising on television and billboards? - Can we find a better way to allocate our brand budget across a diverse set of advertising platforms, marketing initiatives, and audiences? - How can we improve our existing measurement tools to improve sensitivity and reduce bias? The ideal candidate is both technically deep and intellectually humble.  You enjoy out-of-the-box thinking, and are not afraid to roll up your sleeves to get things done. You prioritize practical solutions over novelty but stay curious about new methods and their tradeoffs. You focus on tangible progress and results, but also have a generous spirit, giving others the benefit of the doubt and actively seeking to understand their perspectives. **What you’ll do** - Apply statistical/econometric methods to estimate the incremental impact of changes in marketing and product strategy on brand-relevant KPIs like sentiment, awareness, and purchase intent – as well as on business outcomes like trips/orders and gross bookings. - Build and improve technical tools for marketing problems.  Examples include media mix models, statistical estimators to gauge the impact of various interventions (experimental or otherwise), optimization engines that determine how to best distribute resources, etc. - Interface closely with external partners (media agencies, advertising platforms, measurement vendors) to deeply understand the existing capabilities and limitations of their platforms and solutions, and to push the envelope on what i
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