Data Science - Marketplace Optimization

Uber Overview

Are you interested in working at the intersection of applied quantitative research, engineering development, and data analytics? Do you have interest in developing and applying quantitative solutions related to Uber’s problems? If so, then this is the job for you.

Marketplace Data Scientists embed with Uber’s various marketplace related product and engineering initiatives to help them solve advanced quantitative issues in real-time systems. These fascinating and challenging problems include: building Uber’s dynamic pricing engine; identifying and predicting city specific traffic, travel, and demand patterns; optimizing the assignment process of matching/dispatching drivers to riders; and matching multiple riders to a driver for our UberPool product. Marketplace Data Scientists have the opportunity to tackle some of Uber’s most innovative and impactful problems relating to the operational execution and economic decisions of the business.

However, with great opportunity comes great expectations – this isn’t the job for everyone. We are looking for people with advanced quantitative degrees who are comfortable enough with research methodologies that they can tackle abstract business and engineering problems with extreme precision, and who have the enthusiasm and initiative necessary to deliver those answers at Uber’s breakneck pace. You should have demonstrable programming skills (Python experience is even better) and be comfortable with the engineering development process – you’ll be working on engineering teams.

Marketplace Data Scientists focus strongly on the mathematics and engineering related to optimizing the economics and operations of Uber’s marketplace. Therefore, particular preference is given to candidates with backgrounds in Economics, Econometrics, Operations Research, Operations Management, Industrial Engineering, Statistics, or similar.

Here are the kinds of skills we are looking for:

  • Minimum 1 year practical data science or engineering work experience out of school, in the aforementioned domains’
  • Strong quantitative background: MS or PhD preferred.
  • Familiarity with technical tools for analysis – Python (with Pandas, etc.), R, SQL
  • Programming chops – demonstrable familiarity (work experience, Github account) with programming concepts. Python skills and previous software engineering background a plus.
  • Research mindset – ability to structure a project from idea to experimentation to prototype to implementation.
  • Driven and focused self-starters, great communicators, amazing follow-through – you aggressively tackle your work and love the responsibility of being individually empowered.
  • A preference for quality over quantity – you get the math right and aspire to build the right solution; you like a team that holds each other to a high bar.


  • Employees are given Uber credits every 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.

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.

Back to top