Senior Data Scientist: Real-Time ML & Impact

Uber; New York (NY); On-site; USD 190,000 - 211,000; Full time

Benefits offered by this job

Bonus program

Equity

401(k) plan

Job summary

Uber’s Science team in New York City seeks a seasonedApplied/Data Scientist to turn unstructured data into actionable plans, guiding product and operations with defensible, data-driven decisions. You’ll own lifecycle projects from concept to production, balancing speed with rigor in a fast-moving environment.

You will design experiments, build scalable ML and optimization models, and partner with product, engineering, and operations to unlock growth opportunities and measure impact across the

Qualifications

• Ph.D., MS or Bachelor's degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields.

Responsibilities

• Develop data-driven business insights by collaborating across disciplines: product, engineering, and operations to identify growth opportunities and prioritize initiatives.
• Build and scale statistical, optimization, and machine learning models for strategic insights and real-time production improvements.
• Design and analyze experiments using A/B testing and causal inference to drive decision-making.
• Unblock technical barriers by creating logging, metrics, and diagnostic tools to guide data-driven product development.
• Define how teams measure success by developing robust metrics with cross-functional partners.
• Lead through influence by communicating complex findings to leadership and teams.

Skills

Programming languages (R, Python, Java

Programming languages (Ruby, Scala/SF)

Spark

Hive

HDFS

Experiment design

Education

Ph.D./MS/Bachelor in quantitative field

Tools

Spark

Hive

HDFS

Job description

Uber’s Science team in New York City seeks a seasonedApplied/Data Scientist to turn unstructured data into actionable plans, guiding product and operations with defensible, data-driven decisions. You’ll own lifecycle projects from concept to production, balancing speed with rigor in a fast-moving environment.

You will design experiments, build scalable ML and optimization models, and partner with product, engineering, and operations to unlock growth opportunities and measure impact across the