Staff Scientist, Marketplace (Multiple Teams)

Uber

Hybrid

Quick summary

Work type: Hybrid
Location: San Francisco, CA · New York, NY · Sunnyvale, CA
Salary: $216,000–$216,000 / yr
Posted: 36 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $190k

This role $216k

$132k most similar roles pay here $250k

This role pays more than 80% of similar roles. Most pay $165,000–$214,500 — the shaded band above. At the midpoint, this role pays about $216k versus about $190k for comparable roles.

Based on 240 similar postings.

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 95 open roles on FindRole.

Listed pay typically runs $232,000–$232,000 across 76 roles with salary data.

Most-posted roles

View all roles at Uber

At a glance

TL;DR · Staff Scientist, Marketplace (Multiple Teams)

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As a Staff Scientist at Uber, you will join one of several dynamic teams responsible for driving innovation in areas such as the delivery marketplace, maps, and experimentation platforms. Your role involves formulating complex business problems through data-driven approaches, including causal inference, optimization, and machine learning, while owning the end-to-end product development cycle from data to science aspects. You will mentor team members on critical scientific challenges, develop insights that inform strategic decisions, design experiments, and create tools for data visualization and diagnostic analysis. The position requires expertise in Python or similar languages, proficiency in SQL, and experience with large datasets and statistical modeling. Ideal candidates have a Ph.D. or extensive industry experience in quantitative fields like economics or statistics, along with strong communication skills to lead initiatives across multiple product areas.

Skills

Python R Java Scala SQL Causal Inference Optimization Machine Learning Experiment Design Data Visualization Metrics Development Statistical Analysis Algorithm Prototyping Large-Scale Marketplace Algorithm Design CI/CD

What you'll do

Solve ambiguous business problems using data-driven approaches including causal inference and machine learning.
Own the product development cycle from data collection to analysis and experimentation.
Develop statistical methodologies to enhance experiment validity and generalizability.
Design and analyze experiments to provide actionable recommendations for decision-making.
Mentor team members on critical science problems and thought leadership practices.
Create tools and paradigms for data-driven product development, including metrics and diagnostics.

What we're looking for

Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or related quantitative fields.
7+ years of industry experience as an Applied or Data Scientist (or 4+ with a Ph.D.).
Experience designing and analyzing experiments to draw actionable conclusions from data.
Proficiency in Python or R for statistical analysis and algorithm prototyping.
Strong background in at least one programming language (Python, R, Java, Scala/Spark).
Excellent communication skills to lead initiatives across multiple product areas and present findings.

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