Data Scientist II, ML & Optimization for Scale

Uber; Sunnyvale (CA); Hybrid; USD 225,000 - 270,000; Full time

Job summary

Uber is seeking a Senior Data Scientist in Sunnyvale to turn massive data into actionable insights, influencing pricing, incentives, and user experience. You will build ML models, design experiments, and present results to senior management in a fast-paced environment.

The role emphasizes end-to-end productionization and cross-functional teamwork across product, engineering, and operations. The team values statistical rigor and scalable solutions, with opportunities to work on real-world

Qualifications

• Master's degree plus 3 years of experience in related occupation.
• Data manipulation, unstructured data handling, and creating informative visualizations.
• Experience translating data-driven insights into visuals for senior management.

Responsibilities

• Use data to understand product performance and identify improvement opportunities.
• Build statistical, optimization, and ML models for pricing and incentives.
• Design and run product experiments and interpret results for actionable conclusions.
• Present findings to senior management to inform decisions.
• Collaborate with cross-functional teams to drive end-to-end system development.
• May telecommute.

Skills

Data manipulation

Data visualization

Large-scale data

Dashboards (self-serve)

Python

Experiment design

Causal inference

Machine learning modeling

Optimization & simulation

Education

Master's degree in Statistics, Engineering, Computer Science, Operations Research, or related field

Tools

Tableau

Looker

Git

SQL

Job description

Uber is seeking a Senior Data Scientist in Sunnyvale to turn massive data into actionable insights, influencing pricing, incentives, and user experience. You will build ML models, design experiments, and present results to senior management in a fast-paced environment.

The role emphasizes end-to-end productionization and cross-functional teamwork across product, engineering, and operations. The team values statistical rigor and scalable solutions, with opportunities to work on real-world