Staff Scientist
3 maanden geleden
**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 through:
- 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
**About the Role**
You'll be the Science Tech Lead Manager for Maps in AMS, working closely with Engineering and Product leads to create and execute the direction of the product development in Maps. This includes crafting machine learning, statistics, or analytical solutions to achieve business goals, guiding the team's direction through data-driven insights and algorithmic thinking, and managing scientists and providing them with feedback on their work.
**What You'll Do**
- Work closely with Engineering and Product leads to develop technical vision and drive the team direction through identifying opportunities and building data-driven solutions.
- Develop creative solutions and build prototypes to business problems using algorithms based on machine learning and statistics. Propose and guide framework of data analysis and experiments to drive business insight and facilitate decisions.
- Collaborate closely with Engineering and Product teams to productionize models, enhance data observability and metrics, and conduct experiments and in-depth analysis.
- Provide technical and professional guidance, mentorship, and people management for data scientists.
- Communicate with leadership and cross-functional teams, including presentation of the Science team's work on models, solutions, and data analytics findings.
**Basic Qualifications**
- M.S.'s degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
- 5+ years of industry experience as an (Applied / Data) Scientist or equivalent (3+ years if holding a Ph.D. degree).
- Experience with exploratory data analysis, statistical analysis and testing, causal analysis and ML model development.
- 1+ years of experience in managing a team of Applied / Data Scientists.
- Experience in experimental design and analysis.
- Proficiency using Python, Spark at scale with large data sets.
- Experience with tools like SQL, R in a production environment.
**Preferred Qualifications**
- Ph.D. Degree in Statistics, Machine Learning, Operations Research, or other quantitative fields.
- Experience in tech or marketplace industries.
- Proficiency in programming languages such as Java.
- Experienced in partnering with cross-functional stakeholders to execute decisions.
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