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2021 Ph.D. University Graduate – Data Scientist 1357 views

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

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

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. They also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

About The Role

As a Data Scientist in the Core Analytics & Science (CAS) Team, you’ll answer high impact open questions, prototype cutting edge algorithms, engage in large scale experimentation, and drive business insights through data. You will be collaborating closely with Products, Ops, Engineering, and other Data Scientists and Product Analysts to own and drive a large part of the Uber products and services that have become so ingrained in the daily lives of their customers and partners.

CAS is their largest data science organization, covering both of Uber’s main lines of business as well as the underlying platform technologies that power those businesses. They are a key part of Uber’s cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise.

Here Are The Teams That Make It Happen

  • Eats: Uber Eats is Uber’s ambitious and rapidly growing on-demand food delivery business currently operating in over 45 countries globally and is the largest outside of China. Eats is a 3-sided marketplace, comprising Eaters, Delivery Partners, and Restaurants. Data scientists on Eats come from a variety of technical backgrounds and work on exciting and impactful projects that advance their algorithms and improve engagement with eaters, merchants, and couriers. Projects include optimizing their eater pricing systems and routing algorithms, modeling and predicting eater and courier behavior on the platform, and improving the efficiency of user acquisition, promotions, courier experience, and merchant onboarding.
  • Rides: Rides Data Science at Uber uses data to improve and automate all aspects of Uber’s core ridesharing products. Rides Data Scientists tackle 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 their network, optimizing pickup and dropoff experiences for both riders and drivers, and developing algorithms and experimentation to make their rider and driver user experience stand out. They also forecast, monitor, and evaluate their marketplace and user behavior using both large scale observational data and meticulous experimentation.
  • Platform: Platform Data Science develops the common systems and technical foundations that power Uber’s trip experiences externally and core decision making systems internally. Platform Data Scientists work on building statistical, machine learning, and optimization models for problems like travel time estimation, route optimization, search personalization and ranking, and experimental design and analysis for new algorithm/feature/product launches.

What You’ll Do

  • Tackle ambiguous, exciting business problems using data-driven approaches
  • Work with engineers and product managers to turn data science prototypes into robust, reliable solutions
  • Present findings to business leaders to inform decisions
  • Establish standard methodologies for data science including modeling, coding, analytics, optimization, and experimentation
  • Leverage data to understand the product performance and identify improvement opportunities
  • Build intelligent products to provide the best user experience

Basic Qualifications

  • Currently enrolled in a Ph.D. degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields with an anticipated graduation date in Fall 2020 or Spring/Summer 2021
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
  • Experience with exploratory data analysis, statistical analysis, and testing, and model development
  • Proficiency in languages like SQL, R, and Python

Preferred Qualifications

  • Ability to communicate effectively with both technical and business partners
  • Experience in experimental design and analysis (e.g., A/B and market-level experiments), as well as causal inference
  • Proficiency with Java
  • Previous industry experience (i.e. internships)

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