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Applied Scientist, Marketing Measurement

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Uber

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Location:
United States , New York ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

161000.00 - 179000.00 USD / Year
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Job Description:

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

Job Responsibility:

  • 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 measurement and investment frameworks

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

Nice to have:

  • 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
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • All full-time employees are eligible to participate in a 401(k) plan
  • Eligible for various benefits

Additional Information:

Job Posted:
February 17, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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