Data Scientist - Safety

US-CA-San Francisco
Engineering - Data Science

Uber Overview

About Uber


We’re changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of more than 600 cities around the world. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.


For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.


And that’s just what we’re doing today. We’re thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we’re in for the long haul. We’re reimagining how people and things move from one place to the next.


Job Description

As a data scientist on the Safety Data Science team you will have the opportunity to take on some of the hardest problems in all of Uber: improving the safety of cities and people all over the world.  You will develop expertise and insights in a team that aims to make rare events even rarer.  It is an incredibly challenging, stimulating, and, most of all, rewarding endeavor.

This data scientist will be based at Uber’s HQ in San Francisco, and report to the Sr. Manager in charge of Safety Data Science.  This is a critical and integral opportunity with Uber.  This team has long and successful relationships with our Machine Learning Platform, Insurance, Safety Research, Trust and Risk, Operations, all of our regional teams, and many other parts of Uber.

What you’ll do

  • Master safety-related data, risk factors, and outcomes in high and low resolution, such as before, during, and after a trip, and at coarser aggregations or spans of time and geography
  • Develop and lead statistical and machine learning efforts in relation to your projects.  Our projects leverage machine learning, experimentation, signal processing, time series analysis, geospatial analysis, natural language processing, and more.  We’ll give you as many challenges as you can tackle and help you grow to take on more
  • Leverage large scale data processing such as Spark, Hive, and Uber’s proprietary machine learning platform, and more
  • Work with sensor and telematics data such as GPS and phone accelerometer & gyroscope data
  • Conduct original analyses to inform and influence product, engineering, and operations efforts

What you’ll need

  • We are hiring for all levels of expertise - whether you have 1 year or 20 years of experience, we have problems with the difficulty and scale that will challenge you
  • Solid expertise and creativity in the application of machine learning and statistics
  • Expertise with R or Python
  • Experience as a data scientist at a company with global operations is a big plus
  • Previous experience in safety or risk a plus
  • Demonstrable familiarity with code and programming concepts
  • Experience with production systems or mobile signal processing are a plus
  • Experience with systems like Spark, Hive, SQL, or stream processing are a plus
  • Great communication skills, organized, able to multitask and be a team player
  • Balance attention to detail with swift execution
  • Hunger and drive to learn complex topics
  • Enthusiasm about Uber and the riders, drivers and markets we serve!




  • Employees are given Uber credits every month.
  • The rare opportunity to change the way the world moves. We're not just another social web app, we're moving real people and assets and reinventing transportation and logistics globally.
  • Smart, engaged co-workers.



  • 401(k) plan, gym reimbursement, nine paid company holidays.
  • Full medical/dental/vision package to fit your needs.
  • Unlimited vacation policy; take time when you need it.


Uber is an equal opportunity employer and enthusiastically encourages people from a wide variety of backgrounds and experiences to apply. Uber does not discriminate on the basis of race, color, religion, sex (including pregnancy), gender, national origin, citizenship, age, mental or physical disability, veteran status, marital status, sexual orientation or any other basis prohibited by law.


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