Scientist II, Marketplace (Multiple Teams)

Uber

Hybrid

Quick summary

Work type
Hybrid
Location
New York, NY · San Francisco, CA · Sunnyvale, CA
Posted
9 days ago

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Salary context

How this pay compares to similar roles

Similar $182k
$121k most similar roles pay here $233k

This listing doesn't post a salary. Most similar roles pay $150,000–$214,500.

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.

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At a glance

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

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As a Scientist II on multiple teams within Uber’s Data Science department, you will tackle complex business challenges by formulating data-driven solutions through machine learning, optimization, and causal inference. Your day-to-day responsibilities include developing statistical methodologies to enhance the validity of results, creating data insights, designing experiments, and collaborating with cross-functional teams to prioritize initiatives. You will also drive product development cycles from a data and science perspective, ensuring that success metrics are well-defined and aligned across various business units. The role requires expertise in Python or R for large-scale data analysis and model prototyping, along with strong SQL skills. Ideal candidates have a background in economics, statistics, machine learning, or operations research, and experience in areas such as marketplace algorithm design, consumer growth, or experimentation platforms.

Skills

Python R Java Scala SQL ML Optimization Causal_Inference Experimentation_Platform CI/CD Kubernetes AWS Docker Terraform PostgreSQL MESOS Hadoop Spark Prometheus Grafana

What you'll do

  • Solve ambiguous business problems using ML, optimization, and causal inference.
  • Develop and implement statistical methodologies to enhance results validity and generalizability.
  • Design and analyze experiments, presenting actionable recommendations based on findings.
  • Create data-driven insights and recommend prioritization of initiatives for product growth.
  • Drive the development of logging, metrics, visualization tools, and experimentation paradigms.
  • Define success measures in collaboration with cross-functional partners.

What we're looking for

  • Ph.D., M.S. or Bachelor's degree in a quantitative field like Economics, Statistics, Machine Learning, or Operations Research.
  • 2+ years of industry experience as an Applied or Data Scientist or equivalent technical role (Ph.D. holders exempt).
  • Proficiency in Python or R for data analysis and algorithm prototyping with large datasets.
  • Ability to design experiments and interpret results across various performance indicators.
  • Experience in developing statistical methodologies and algorithms to enhance model validity and generalizability.
  • Strong background in programming languages such as Python, R, Java, Scala/Spark for efficient data handling.

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