Applied Scientist / Senior Applied Scientist - Applied Machine Learning or Operations Research at Uber (San Francisco, CA)

| San Francisco, CA
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About CAS
The Core Analytics & Science Team (CAS) is Uber's largest data and applied sciences organization, covering both of Uber's main lines of business as well as the underlying platform technologies that power those businesses. We 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.
Applied Machine Learning or Operations Research Applied Science
Here are the teams that make it happen:
Eats: Uber Eats is Uber's ambitious and rapidly expanding on-demand food delivery business currently operating in more than 45 countries globally and is the largest outside of China. Applied Machine Learning Scientists in Uber Eats solve many exciting problems in the Recommendation, Search and Knowledge Graph space.
Rides: Rides Data and Applied Sciences at Uber uses data to improve and automate all aspects of Uber's core ridesharing products. For drivers, we are 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. For Riders, building products that create an awesome experience for people who ride with Uber. The Fares team calculates and serves prices to all our users.
Platforms: Platform Data and Applied Sciences develops the common systems and technical foundations that power Uber's trip experiences externally and core decision making systems internally. This team develops: the machine learning and AI platforms; the mapping services that perform travel time (ETA) prediction, route optimization, navigation, pickup & dropoff specification, and more; and Uber's customer support and financial technology systems.
About the Role
Here's what's in it for you! As an Applied Scientist in the CAS organization, you have a unique opportunity to use your quantitative skills in statistics, machine learning and economics. 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 Applied Scientists and Data Scientists to own and drive a large part of the Uber products and services that have become so ingrained in the daily lives of our customers and partners.
What You'll Do
  • Leverage data to understand product performance and to identify improvement opportunities
  • Work with engineers and product managers to turn prototypes into robust, reliable solutions
  • Build statistical, optimization, and machine learning models the product efficiency and scalability
  • Deliver real world recommender systems and search ranking models that will critically impact the growth, efficiency, and reliability of Uber's marketplace.
  • Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions that powers all consumer facing products and features on the Uber Eats and/or Rides apps.
  • Conduct research and implementation of novel machine learning and statistical approaches to address medium-to-long term business and product problems
  • Collaborate with cross functional team (engineers, product analysts, product managers, designers) to define the business problem, identify the opportunities, and execute team and product strategies
  • Establish scalable, efficient, automated processes to boost team productivity, such as model development, model validation and model implementation

Basic Qualifications
  • Ph.D., MS or Bachelors degree in, Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative field. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience required)
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
  • Knowledge of experimental design and analysis
  • Experience with exploratory data analysis, statistical analysis and testing, and model development
  • Ability to use a language like Python or R to work efficiently at scale with large data sets
  • Proficiency in languages and tools like SQL, Hive, and Spark

Preferred Qualifications
  • 5+ years of industry experience working as an applied scientist or similar
  • M.S. degree in Statistics, Machine Learning, Operations Research, or other quantitative fields with 3+ years of industry experience
  • Ph.D. in Statistics, Machine Learning, Operations Research, or other quantitative field
  • Experience in experimental design and analysis (e.g., A/B and market-level experiments), causal inference
  • Experience in algorithm development and prototyping
  • Experience with productionizing algorithms for real-time systems
  • Proficiency in Java, Scala, or Go
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