Uber
From Uber's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
About the Role and Team Working in Science at Uber means solving complex marketplace problems in a high-stakes, fast-moving environment.
Working in Science at Uber means solving complex marketplace problems in a high-stakes, fast-moving environment. You will be joining the Rider Pricing and Incentives Science team, which owns our automated real-time pricing systems. You’ll turn massive amounts of unstructured marketplace data into focused algorithmic strategies, navigating ambiguity to build technologies that directly influence every ride decision made across our global mobility marketplace.
In this role, you’ll serve as the vital bridge between technical depth and real-world business impact. We are looking for experienced candidates with strong quantitative expertise across data science, operations research, statistics, and economics. You will thrive here if you possess an owner’s mindset, combine algorithmic rigour with practical execution, and excel at driving complex initiatives through close cross-functional collaboration with product and engineering partners.
Build, scale, and optimize statistical, mathematical programming, and ML models for dynamic pricing applications.
Generate data insights to identify opportunities to enhance algorithm performance.
Develop novel experimentation and causal inference methodologies tailored to complex, highly interconnected marketplace settings.
Collaborate deeply across disciplines with Product, Engineering, and Operations to identify growth opportunities, align on key success metrics, and drive systems end-to-end from ideation to production.
Translate granular marketplace data and complex optimization results into clear, actionable business strategies for leadership.
Unblock technical and operational barriers by designing robust diagnostic tools, logging infrastructure, and marketplace metrics.
Ph.D., M.S., or Bachelor's degree in Operations Research, Data Science, Statistics, Economics, Mathematics, Computer Science, or equivalent quantitative field.
5+ years of professional industry experience as an Applied Scientist, Data Scientist, Economist, or equivalent (or 3+ years with a Ph.D.).
Strong foundation in at least one key domain: control theory, mathematical optimization, statistical inference, machine learning, econometrics.
Proficiency in Python/R and SQL for large-scale data analysis and algorithmic prototyping.
Experience in designing, analyzing, and interpreting complex experiments across key marketplace performance indicators.
6+ years of industry experience applying data science, optimization, or economics in dynamic marketplace or pricing environments.
Demonstrated success partnering closely with Product, Engineering, and Operations partners to deploy algorithms into production.
Hands-on experience building large-scale pricing, auction, advertising, or supply-demand matching algorithms.
Proven track record of navigating ambiguity and communicating technical concepts clearly to non-technical business partners.
For New York City, NY-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
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Hi [Name], I just applied for the Sr Scientist, Tech - Science role at Uber. My background in [your most relevant experience] lines up well with what the team is looking for. Would you be open to a quick chat, or could you point me to the right person on the team? Thank you!
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