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$159,875–$238,750.
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.
The Sr Scientist, Tech - Science joins the Uber Direct science team to solve complex transportation problems within a B2B delivery-as-a-service product. This role involves turning unstructured data into actionable plans by building and scaling statistical, optimization, and machine learning models that provide real-time production enhancements. You will collaborate across product, engineering, and operations to identify growth opportunities, design complex experiments using A/B testing and causal inference, and develop robust metrics to measure success. The position requires proficiency in programming languages such as R, Python, Java, Ruby, Scala/Spark, or Perl, along with experience using Spark, Hive, or HDFS to process large-scale datasets. You will drive high-complexity technical projects from inception to production, translating technical findings into strategic business insights for leadership.
Build and scale statistical, optimization, and machine learning models for global products.
Design and analyze complex experiments using A/B testing and causal inference.
Develop data-driven business insights to identify growth opportunities and prioritize high-impact initiatives.
Create logging, metrics, and diagnostic tools to unblock technical barriers for product development.
Develop robust success metrics in partnership with stakeholders to align on long-term impact.
Communicate complex technical findings and outcomes to leadership and technical partners.
Drive high-complexity technical projects from initial concept through to production.
What we're looking for
Bachelor's, Master's, or Ph.D. degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields.
5+ years of industry experience as an Applied or Data Scientist or equivalent (or 3+ years with a Ph.D.).
Proficiency in at least one programming language such as R, Python, Java, Ruby, Scala/Spark, or Perl.
Experience designing experiments and interpreting results across a variety of key performance indicators.
Ph.D. degree in a quantitative field such as Machine Learning, Operations Research, Economics, or Statistics (preferred).
Outstanding communication skills with a track record of influencing leadership and technical teams through storytelling and data-driven insights (preferred).
Experience leading high-complexity technical projects and substantially influencing the scope and output of others (preferred).
Proven ability to work efficiently with large-scale datasets using Spark, Hive, or HDFS (preferred).
Python
SQL
R
Machine Learning
Mathematical Optimization
Statistical Inference
Causal Inference
Econometrics
Operations Research
Data Science
Control Theory
Data Analysis
Logging Infrastructure
Algorithmic Prototyping