Data Scientist - Seattle

Uber Overview

Uber Seattle works on some of the most interesting problems across Uber. We are truly a collection of startups within a startup. Smart cities for example, is working with cities to make transportation as reliable as running water for everyone by automatically detecting and reporting potholes, dangerous intersections, and even traffic hotspots. UberFamily is finding novel ways to empower individuals to efficiently and safely move around their entire families. The Airports and Venues team is defining the airport pickup experience of the future—imagine a zero touch experience you simply get off a plane and get into your Uber. The Scheduled Rides team is breaking the mold again and has managed to prove out a whole new business vertical. Each of these amazing teams is truly its own self-contained, fully staffed business unit with a singular mission and bias towards action.

As a data scientist working with any of these teams, you will push your comfort zone until you are truly a full-stack data scientist who not only can but constantly and rigorously:

  • Defines and drives analysis which regularly and fundamentally alters vision of the team through deep and holistic understanding of both rider and driver behavior,
  • Develops a myriad of statistical and machine learned models for everything from classification to real-time prediction using a mix of internal and external data,
  • Delivers strategic projects that materially affect the companies overall bottom line,
  • Crafts and monitors the business unit’s KPIs

all in the confines of a real-time two-sided marketplace across the entire world. This role is not for the faint of heart.

Uber is a fast pasted, hyper-growth company filled with the world’s very best and brightest who have a passion to actually change the world. If you want to be the reason that your grandchild cannot fathom how people used to own their own cars, here’s what we’re looking for:

  • Driven and focused self-starters, great communicators, amazing follow-through – you are entrepreneurial and love the responsibility of being individually empowered.
  • 3+ years of highly analytical experience ideally in data science, applied researcher or other like fields.
  • SQL and Hadoop.
  • R or Python.
  • Machine Learning Techniques especially time series, and geospatial.
  • A/B testing especially in two sided market-places
  • Graduate degrees in quantitative background: e.g. Statistics, Computer Science, Math, Operations Research, Applied Psychology, Econometrics, or other technical field.

If you have all that and you are still fun to be around: please come, change the world with us!


  • Employees are showered with Uber credits each month.
  • Ground floor opportunity with the team; shape the strategic direction of the company.
  • The rare opportunity to change the world such that everyone around you is using the product you built. We’re not just another social web app, we’re moving real people and assets and reinventing transportation and logistics globally.
  • Sharp, motivated co-workers in a fun office environment.
  • 401(k) plan, gym reimbursement, nine paid company holidays.
  • Full medical/dental/vision package to fit your needs.
  • Unlimited vacation policy; work hard and take time when you need it.
  • A great office filled with people who love ping-pong tournaments, boat cruises and game nights.

We’re bringing Uber to every major city in the world. We need brains and passion to make it happen and to make it happen in style.

Be sure to check out the Uber Engineering Blog to learn more about the team.

Meet Some of Uber's Employees

Brian M.

Community Management Specialist

Brian makes sure that every Uber user has an amazing experience. He troubleshoots roadblocks to customer happiness and also does outreach to attract new Uber users.

Swathy P.

Operations & Logistics Manager

Swathy is part of the team that is the driving force behind Uber’s transportation options. She helps sign up the drivers, makes sure the vehicles run smoothly, and tackles any logistical bumps along the road.

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