Uber
Senior Scientist - Matching, Membership, Maps, Experimentation
Uber, San Francisco, California, United States, 94199
Senior Scientist - Matching, Membership, Maps, Experimentation
Join to apply for the
Senior Scientist - Matching, Membership, Maps, Experimentation
role at
Uber About The Team
The Delivery Logistics (matching) science team builds large‑scale technologies powering our global marketplace, including real‑time backend matching and scheduling systems, new delivery experiences with intelligent pricing, and predictions such as estimated time to delivery (ETD). The Membership science team designs quantitative models to grow the Uber One program, using causal ML to set benefits, optimize acquisition funnels, prevent churn, and analyze membership value. The Maps science team solves major modeling challenges such as travel‑time prediction, traffic forecasting, route recommendation, and navigation, feeding core trip‑flow and internal decision systems. The Experimentation science team builds the experimentation platform and measurement models, providing reliable, trustworthy, and agile experimentation to support business decisions across Uber. What You Will Do
Solve ambiguous, challenging business problems using data‑driven approaches including ML, optimization, and causal inference. Develop and implement statistical/econometric methods to improve result validity, power, and generalizability. Generate data‑driven insights and collaborate with cross‑functional customers to prioritize product, growth, and optimization initiatives. Design and analyze experiments and present actionable recommendations. Drive data‑driven product development by establishing logging, metrics, data visualization, and experimentation paradigms. Define success metrics in partnership with cross‑functional partners. Own the end‑to‑end product development cycle from data and science perspectives. Basic Qualifications
Ph.D., M.S., or Bachelor’s degree in Economics, Statistics, Machine Learning, Operations Research, or another quantitative field. 4+ years of industry experience as an applied or data scientist, or 2+ years with a Ph.D. Proficiency in at least one programming language (Python, R, Java, Ruby, Scala/Spark, or Perl). Ability to work efficiently with large datasets and prototype algorithms and models using Python or similar technologies. Strong coding and SQL skills for statistical analysis and algorithm prototyping in Python or R. Experience designing experiments and interpreting results to deliver detailed, actionable conclusions across key performance indicators. Preferred Qualifications
Ph.D. in Economics, Statistics, Machine Learning, Operations Research, or a related field. Excellent communication and collaboration skills, with the ability to lead initiatives across multiple product areas and communicate findings to leadership and product teams. Experience leading key technical projects and influencing the scope and output of others. Thought leadership driving multi‑functional projects from concept to production. Experience in large‑scale marketplace algorithm design, membership/consumer growth, or experimentation platforms. Proficiency in exploratory data analysis, statistical analysis, and model development. Strong programming skills to prototype models in Python (preferred), R, Java, Go, or Scala. Compensation & Benefits
For New York, NY–based roles: base salary range USD $183,000 – USD $203,000 per year. For San Francisco, CA–based roles: base salary range USD $183,000 – USD $203,000 per year. For all U.S. locations, candidates are eligible to participate in Uber’s bonus program, may be offered an equity award and other compensation types, and are eligible for various benefits. Further details can be found at
Uber Careers Benefits . Seniority Level
Mid‑Senior level Employment Type
Full‑time Job Function
Research, Analyst, and Information Technology Industries
Internet Marketplace Platforms
#J-18808-Ljbffr
Join to apply for the
Senior Scientist - Matching, Membership, Maps, Experimentation
role at
Uber About The Team
The Delivery Logistics (matching) science team builds large‑scale technologies powering our global marketplace, including real‑time backend matching and scheduling systems, new delivery experiences with intelligent pricing, and predictions such as estimated time to delivery (ETD). The Membership science team designs quantitative models to grow the Uber One program, using causal ML to set benefits, optimize acquisition funnels, prevent churn, and analyze membership value. The Maps science team solves major modeling challenges such as travel‑time prediction, traffic forecasting, route recommendation, and navigation, feeding core trip‑flow and internal decision systems. The Experimentation science team builds the experimentation platform and measurement models, providing reliable, trustworthy, and agile experimentation to support business decisions across Uber. What You Will Do
Solve ambiguous, challenging business problems using data‑driven approaches including ML, optimization, and causal inference. Develop and implement statistical/econometric methods to improve result validity, power, and generalizability. Generate data‑driven insights and collaborate with cross‑functional customers to prioritize product, growth, and optimization initiatives. Design and analyze experiments and present actionable recommendations. Drive data‑driven product development by establishing logging, metrics, data visualization, and experimentation paradigms. Define success metrics in partnership with cross‑functional partners. Own the end‑to‑end product development cycle from data and science perspectives. Basic Qualifications
Ph.D., M.S., or Bachelor’s degree in Economics, Statistics, Machine Learning, Operations Research, or another quantitative field. 4+ years of industry experience as an applied or data scientist, or 2+ years with a Ph.D. Proficiency in at least one programming language (Python, R, Java, Ruby, Scala/Spark, or Perl). Ability to work efficiently with large datasets and prototype algorithms and models using Python or similar technologies. Strong coding and SQL skills for statistical analysis and algorithm prototyping in Python or R. Experience designing experiments and interpreting results to deliver detailed, actionable conclusions across key performance indicators. Preferred Qualifications
Ph.D. in Economics, Statistics, Machine Learning, Operations Research, or a related field. Excellent communication and collaboration skills, with the ability to lead initiatives across multiple product areas and communicate findings to leadership and product teams. Experience leading key technical projects and influencing the scope and output of others. Thought leadership driving multi‑functional projects from concept to production. Experience in large‑scale marketplace algorithm design, membership/consumer growth, or experimentation platforms. Proficiency in exploratory data analysis, statistical analysis, and model development. Strong programming skills to prototype models in Python (preferred), R, Java, Go, or Scala. Compensation & Benefits
For New York, NY–based roles: base salary range USD $183,000 – USD $203,000 per year. For San Francisco, CA–based roles: base salary range USD $183,000 – USD $203,000 per year. For all U.S. locations, candidates are eligible to participate in Uber’s bonus program, may be offered an equity award and other compensation types, and are eligible for various benefits. Further details can be found at
Uber Careers Benefits . Seniority Level
Mid‑Senior level Employment Type
Full‑time Job Function
Research, Analyst, and Information Technology Industries
Internet Marketplace Platforms
#J-18808-Ljbffr