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Data Scientist – Marketplace Matching Optimization 834 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 the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

About The Role

The matching team directly contributes to Uber’s growth and profitability by deciding how rider requests should be matched with drivers.

Uber’s matching mechanism has evolved from greedy dispatch to global batch optimization to joint optimization across different products including rides and eats

As a Data Scientist in the Core Matching team, you’ll be working on analyzing and designing the key algorithms behind Uber’s matching algorithm, both to increase the efficiency of the marketplace and to enable new growth verticals.

What You’ll Do

  • Build statistical, optimization, and machine learning models for applications including pricing, matching, routing, automated recommendations, growth strategies, and user behavior modeling
  • Design product experiments and interpret the results to draw detailed and actionable conclusions
  • Leverage data to understand the product performance and to identify improvement opportunities
  • Present findings to senior management to inform business decisions
  • Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization.

Basic Qualifications

  • Ph.D., M.S., B.S. or B.A. degree in Statistics, Mathematics, Economics, Operations Research, Computer Science, Physics or other quantitative fields (Bachelors at least 4+ yrs of relevant product experience)
  • Proficient in languages like Python, R, or Java to work efficiently at scale with large data sets
  • Experience with algorithm development, exploratory data analysis, statistical analysis, or machine learning model development

Preferred Qualifications

  • Advanced knowledge of experiment design, statistical methods, and optimization technique
  • Experience with productionizing algorithms
  • Worked on supporting consumer-facing products
  • Ability to effectively manage relationships with stakeholders coming from both technical and non-technical backgrounds

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