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2020 PhD Data Scientist Internship - Rides

Data Science, University
Seattle, Washington |
San Francisco, California

About the Role

We're looking for PhD intern candidates to intern during summer 2020 (3 months). You would be contributing to Rides Data Science, which encompasses all teams responsible for working on moving people from A -> B. We seek candidates with various backgrounds -- economics, machine learning, statistics, computer science, operations research, etc. You will be embedded in a product team -- Rider Pricing, Matching, Driver, etc., -- and work closely with other data scientists, engineers and product managers under the supervision of a data scientist on that team. You'll be focused on modeling and algorithm development on a project defined by you and your mentor.

We are hiring interns for our San Francisco and Seattle offices.

What You'll Do

  • Work with your mentor closely to scope a project, define the problem, and develop and prototype the solution
  • Work alongside engineers and product managers to understand the business use cases and production feasibility of your work, and collaborate on the experimentation and productionisation of your work
  • Develop creative solutions to product problems using a combination of empirical insights and sophisticated technical methods
  • Communicate with senior management and cross-functional teams

Sample Projects

  • Simulate the effects of re-allocating between driver incentive mechanisms
  • Investigate how surge pricing interacts with different innovations in how riders are matched with drivers
  • Develop new matching algorithms that power our shared rides products.
  • Build matching algorithms to enable transportation solutions in different markets
  • Quantify the medium- to long-term impact of changes to pricing and matching on rider and driver partner activity.
  • Build machine learning models which predict a customer's response to promotions.
  • Investigate the meaning and impact of trip quality on riders and drivers
  • Build uplift and segmentation models to be used for targeted outreach and re-engagement strategies
  • Build machine learning models for product selection, hotspot location and routing optimization
  • Build OCR models to automate driver document transcription
  • Build models to optimize our fleets of bikes and scooters

What You'll Need

  • Ph.D. student (anticipated graduation in December 2020-summer 2021) majoring in CS, Economics, Statistics, Machine Learning, Operations Research, or other quantitative disciplines
  • Experience in modeling and algorithm development
  • Coding proficiency and the ability to develop statistical analysis and prototype algorithms in Python or R
  • Proficiency in SQL to query large datasets
  • Ability to communicate effectively with both technical and business stakeholders

About the Team

In Rides you'll be at the center of Uber's business, where riders and drivers come together at an extraordinary scale. As a data scientist, you'll combine clear product vision, deep technical skills and powerful data analysis to improve the algorithms that run Uber's vast worldwide marketplace every minute of the day. We're looking for you to produce elegant solutions that are practical, effective, and can work at Uber scale.

Our team tackles problems such as optimizing Uber's short and long term pricing systems; efficiently matching incoming trip requests in Uber's dispatch system; developing innovative incentive schemes that reward riders and drivers for choosing our network; optimizing pickup and dropoff experiences for both riders and drivers, and providing optimal routes and accurate turn-by-turn navigation to save time for everybody. We also forecast, monitor and evaluate all aspects of our marketplace using both large scale observational data and rigorous experimentation.

If you are passionate about original ideas, and take pride in seeing those thoughts come to life in a high impact setting, then you'll be at home in our team where creative exploration and iterative experimentation are at the heart of what we do. As part of Rides, you will work side-by-side with Uber's engineering team to scale your ideas across Uber's real-time production systems, and then strive to gain insights from the real world outcomes we measure.

About the Subteams

  • Maps: Mediating users' digital connection to their physical world through traffic modeling, travel time estimation, route optimization, geospatial search, hotspot computation, and navigation
  • Experimentation: Develop statistical methods and implement them in scalable tools for teams to run both user level ABs and market level experiments that deal with network interference
  • Driver: Creating a seamless product experience for drivers across the driver journey: matching drivers to cars, onboarding onto our platform, creating a stress free trip experience
  • Matching: Building and optimizing matching algorithms and new matching paradigms across Uber to increase efficiency, reduce ETAs, and reduce prices across Uber's ridesharing marketplace
  • Pricing, Incentives and Loyalty: Building and optimizing pricing and incentive algorithms for riders and drivers, measuring effectiveness using A/B and market level designs
  • Airports:The Airports team is part of the Rider Verticals organization and looks after riders, drivers, marketplace, airports, and operations for rides at airport venues. The Rider Verticals team also looks after Premium, Scheduled, and Events businesses around the world. Across these verticals we work to build more intelligent systems to improve rider and driver experiences using machine learning, optimization, analytics, and testing.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.