About The TeamThe 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.If you're passionate about driving innovation and have relevant experiences in tech or marketplace settings, we sincerely welcome you to join our team and shape the future of Uber's geospatial technologies together.You Can Learn More About Our Team From Fixing Map Errors with GPS Data What's my ETA? A Billion $ question Rethinking GPS: Engineering Next-Gen Location at Uber Enhancing the Quality of Uber's Maps with Metrics Computation Applying Customer Feedback: How NLP & Deep Learning Improve Uber's Maps What You Will Do 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. Basic Qualifications 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. Preferred Qualifications 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.