Responsibilities

• 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

Requirements

• Bachelor's degree or higher in a quantitative field such as Statistics, Economics, Mathematics, Computer Science, or a related discipline.
• 2+ years of experience applying statistical and causal inference methods to real-world data in an applied setting.
• Strong foundation in statistical modeling, hypothesis testing, and experimental design, including A/B testing, incrementality, or quasi-experimental methods.
• Hands-on experience designing, analyzing, and interpreting experiments, including evaluation of uncertainty, limitations, and tradeoffs.
• Proficiency in Python or R and SQL for analyzing and modeling large, complex datasets.
• Experience working with marketing, growth, advertising, or similar business domains where measurement and investment decisions are central.
• Ability to clearly communicate analytical insights to technical and non-technical stakeholders and collaborate effectively in cross-functional teams.
• Demonstrated ability to collaborate effectively in cross-functional, fast-moving environments.

Preferred

• Bachelor's, Master's or PhD in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Computer Science), or equivalent applied industry experience.
• Experience with advanced statistical or modeling techniques such as hierarchical / multi-level models, time-series analysis, or meta-analysis.
• Experience with incrementality testing, geo-experiments, or marketing measurement use cases (e.g., attribution, MMM, or related frameworks).
• Familiarity with marketing investment concepts such as elasticity, budget allocation, or cross-channel tradeoffs.
• Experience contributing to shared codebases or production-adjacent analytics systems, including collaboration with Product or Engineering partners.
• Ability to independently drive scoped projects end-to-end with guidance, and operate effectively in ambiguous or evolving problem spaces.
• Curiosity and learning mindset, with demonstrated ability to ramp quickly on new domains, tools, or methodologies.

Benefits

• More details can be found at the following link.