Senior Applied Scientist - Brand Marketing

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.

As a member of the Brand Science team, you will not only be able to perform complex analyses exploring our rich dataset, but also shape marketing and measurement strategy. You'll play a big part in finding opportunities to help the marketing function scale as we develop the global Uber brand.

What the Candidate Will 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 is possible.
• Collaborate with our in-house media, research, product, and operations teams to develop actionable customer insights and recommendations to guide high level business and marketing strategy.

• 5+ years of experience (or equivalent) with statistical modeling, causal inference, and econometric techniques.
• Proficiency in SQL and a data analysis programming language - Python (preferred) or R
• Excellent communication skills to understand stakeholder needs, set expectations around feasibility, translate business challenges into research questions, and present findings to technical and non-technical audiences
• Be self-driven and show the ability to deliver on ambiguous projects with messy and incomplete data

• Experience with solving quantitative problems in the marketing/AdTech space
• PhD in a quantitative field such as statistics, economics, or operations research
• Intellectual curiosity and a knack for applying/extending technical solutions in innovative ways