About the Team
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.
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.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let’s move it forward, together.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.