Staff Scientist, Tech

Uber

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: New York, NY
Posted: 56 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $214k

$139k $285k

below market most similar roles pay here above market

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Employer

About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

Uber currently has 107 open roles on FindRole.

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At a glance

TL;DR · Staff Scientist, Tech

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The Staff Scientist, Tech - Science joins the Earner Program Logistics team to solve high-stakes optimization and marketplace problems at the boundary of digital algorithms and physical-world delivery. This role serves as a principal technical multiplier, shaping the science strategy for core marketplace decisions to ensure algorithms optimize for long-term platform value and incentive compatibility. You will lead the end-to-end scientific vision for complex logistics systems, translating unstructured problems into rigorous experiments and productionized solutions. Key responsibilities include driving product development using Causal Inference and Optimization, setting experimentation standards, and influencing executive-level roadmaps. Required skills include proficiency in SQL and Python, experience with Spark, Hive, and Presto, and deep expertise in statistical inference, experimental design, and marketplace optimization for global eaters, merchants, and couriers.

Skills

Causal Inference Optimization Python SQL Spark Hive Presto Experimental Design Statistical Inference Operations Research Statistics Applied Mathematics Marketplace Optimization

What you'll do

Translate unstructured business problems into rigorous experiments and productionized solutions.
Drive the end-to-end product development lifecycle using Causal Inference and Optimization.
Set science strategies and experimentation standards to ensure organization-wide scientific rigor.
Identify opportunities to improve model performance, efficiency, and technical debt reduction.
Present complex technical findings and long-term strategic recommendations to senior leadership.
Own the technical trajectory of critical product areas to ensure extensible and modular designs.
Design algorithms that optimize for long-term platform value and incentive compatibility.

What we're looking for

Bachelor's, Master's, or Ph.D. degree in Operations Research, Economics, Statistics, Applied Mathematics, or other quantitative fields.
Minimum of 6 years of industry experience for an M.S. degree.
Minimum of 8 years of industry experience for a B.S. degree.
Deep expertise in statistical inference and experimental design, such as A/B testing and cluster-randomized trials.
Proficiency in SQL and Python to work with large-scale datasets and distributed tools like Spark, Hive, and Presto.
Track record of foreseeing architectural or scientific problems 12+ months out (preferred).
Experience leading multi-quarter, cross-functional initiatives that moved significant marketplace or financial metrics (preferred).
Specialized expertise in Causal Inference at scale, Economics, or Marketplace Optimization (preferred).

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