This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
The Uber Maps team is at the forefront of advancing Uber’s geospatial technologies, crucial for driving the efficiency and reliability of Uber services. We work across a diverse array of problem domains, including: curating and improving precision of location (i.e. ‘Places’) data, developing cutting-edge location search algorithms for each Rides pickup/dropoff and Eats delivery, building base maps and correcting map errors, as well as optimizing routes and travel time predictions, and more. These pivotal technologies are the backbone of every decision made in our marketplace, influencing dispatch and pricing strategies directly.
Job Responsibility:
Develop data-driven business insights and work with cross-functional customers to find opportunities and recommend prioritization of product, growth, and optimization initiatives
Build statistical, optimization, and machine learning models for strategic insights as well as in production enhancements to the maps products
Design and analyze experiments, present results that provide actionable recommendations
Orient our teams around data-driven product development by driving the creation of logging, metrics, data visualization and diagnostic tools, and experimentation paradigms
Define how our teams measure success by developing metrics in close partnership with cross-functional partners
Requirements:
Ph.D., M.S. or Bachelor's degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields
5+ years of industry experience as an Applied or Data Scientist or equivalent (or 3+ years with Ph.D.)
Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl)
Develop statistical analysis and prototype algorithms in Python or R
Work efficiently with large data sets using Python, SQL, R or similar
Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators
Nice to have:
Ph.D. degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields
Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
Experience leading key technical projects and substantially influencing the scope and output of others
Solid Programming skills to prototype models in at least one of Python (preferably), R, Java, Go, Scala
Experience of working with large datasets using Spark, Hive, HDFS is desired
Thought leadership to drive multi-functional projects from concept to production