Uber
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Scientist II, Delivery Courier Pricing
role at
Uber .
The Uber Eats Marketplace team is the heart of the Uber Eats business. We build the platform and products that power the magical experience of connecting eaters, couriers, and restaurants. As a critical component of this ecosystem, the Courier Pricing team is responsible for the complex systems that determine courier earnings on every Uber Eats delivery worldwide.
Our mission is to build and refine a fully automated pricing system that optimizes our three‑sided marketplace for consumers, couriers, and merchants. We leverage sophisticated optimization, machine learning, and causal inference techniques to balance efficiency, reliability, and cost under highly dynamic conditions. This is a high‑impact team solving core business challenges across diverse verticals—including restaurant delivery, grocery, and retail—and supporting global markets with unique and complex problems.
What You’ll Do
Design, develop, and deploy models and algorithms (e.g., optimization, machine learning, structural models) to power both structural and real‑time pricing decisions at a global scale.
Lead the end‑to‑end design and analysis of large‑scale experiments to validate models and inform strategic pricing decisions.
Conduct deep‑dive data analysis to uncover critical insights, understand product performance, and identify new opportunities for optimization.
Develop and implement key metrics to monitor, evaluate, and iterate on the performance of our pricing systems, ensuring they meet business objectives.
Partner closely with Product Managers, Engineers, and Operations teams to translate ambiguous business challenges into quantitative problems and shepherd solutions from ideation to production.
What You’ll Need (Basic Qualifications)
A Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Operations Research) OR a Master’s/Bachelor’s degree in a similar field with 2+ years of relevant industry experience.
Proficiency in data analysis and programming using a language like Python or R.
Experience querying databases using SQL.
Foundational knowledge in at least one of the following areas: machine learning, statistics, optimization, causal inference, or economics.
Excellent communication skills, with the ability to convey complex technical concepts to diverse audiences.
Preferred Qualifications
Deep, hands‑on expertise and a proven track record of applying advanced methods from machine learning, statistics, optimization, and causal inference to solve complex, real‑world business problems.
Direct experience in a marketplace or pricing‑related domain (e.g., dynamic pricing, auctions, mechanism design).
Demonstrated expertise in designing and analyzing complex experiments in a production environment.
Strong problem‑solving skills, with a proven ability to translate ambiguous business questions into a structured analytical framework.
Experience with large‑scale data processing tools like Spark, Hive, or Presto.
Compensation & Benefits For New York, NY‑based roles: The base salary range for this role is USD 155,000 per year – USD 172,000 per year. For San Francisco, CA‑based roles: The base salary range for this role is USD 155,000 per year – USD 172,000 per year. For all US locations, you will be eligible to participate in Uber’s bonus program and may be offered an equity award and other types of compensation. You will also be eligible for various benefits. More details can be found at https://www.uber.com/careers/benefits.
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Scientist II, Delivery Courier Pricing
role at
Uber .
The Uber Eats Marketplace team is the heart of the Uber Eats business. We build the platform and products that power the magical experience of connecting eaters, couriers, and restaurants. As a critical component of this ecosystem, the Courier Pricing team is responsible for the complex systems that determine courier earnings on every Uber Eats delivery worldwide.
Our mission is to build and refine a fully automated pricing system that optimizes our three‑sided marketplace for consumers, couriers, and merchants. We leverage sophisticated optimization, machine learning, and causal inference techniques to balance efficiency, reliability, and cost under highly dynamic conditions. This is a high‑impact team solving core business challenges across diverse verticals—including restaurant delivery, grocery, and retail—and supporting global markets with unique and complex problems.
What You’ll Do
Design, develop, and deploy models and algorithms (e.g., optimization, machine learning, structural models) to power both structural and real‑time pricing decisions at a global scale.
Lead the end‑to‑end design and analysis of large‑scale experiments to validate models and inform strategic pricing decisions.
Conduct deep‑dive data analysis to uncover critical insights, understand product performance, and identify new opportunities for optimization.
Develop and implement key metrics to monitor, evaluate, and iterate on the performance of our pricing systems, ensuring they meet business objectives.
Partner closely with Product Managers, Engineers, and Operations teams to translate ambiguous business challenges into quantitative problems and shepherd solutions from ideation to production.
What You’ll Need (Basic Qualifications)
A Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Operations Research) OR a Master’s/Bachelor’s degree in a similar field with 2+ years of relevant industry experience.
Proficiency in data analysis and programming using a language like Python or R.
Experience querying databases using SQL.
Foundational knowledge in at least one of the following areas: machine learning, statistics, optimization, causal inference, or economics.
Excellent communication skills, with the ability to convey complex technical concepts to diverse audiences.
Preferred Qualifications
Deep, hands‑on expertise and a proven track record of applying advanced methods from machine learning, statistics, optimization, and causal inference to solve complex, real‑world business problems.
Direct experience in a marketplace or pricing‑related domain (e.g., dynamic pricing, auctions, mechanism design).
Demonstrated expertise in designing and analyzing complex experiments in a production environment.
Strong problem‑solving skills, with a proven ability to translate ambiguous business questions into a structured analytical framework.
Experience with large‑scale data processing tools like Spark, Hive, or Presto.
Compensation & Benefits For New York, NY‑based roles: The base salary range for this role is USD 155,000 per year – USD 172,000 per year. For San Francisco, CA‑based roles: The base salary range for this role is USD 155,000 per year – USD 172,000 per year. For all US locations, you will be eligible to participate in Uber’s bonus program and may be offered an equity award and other types of compensation. You will also be eligible for various benefits. More details can be found at https://www.uber.com/careers/benefits.
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