Sr. Data Scientist - Driver Movement & Pricing at Uber
About the Role
The driver movement & pricing team maximizes the marketplace efficiency through influencing supply and demand in real time. This involves developing fundamental understandings of driver behavior in the most unique labor market, creating pricing algorithms that incorporate both marketplace dynamics and supply preferences, matching the best supply to the most needed demand in an effective manner. The team has two tracks: 1) The Movement Track influences drivers' offtrip decisions (activation, positioning, offline) through_ Surge, Suggestions, Spatial Heatmap. _2) The Pricing track influence drivers' ontrip decisions (acceptance, rejections, cancellations) through multiple _Pricing, Matching and Preferences levers. _The team utilizes ML, Economic Modeling, Optimization, and relies on continuous exploration and experimentation to make data-driven decisions.
Here's what's in it for you! You have a unique opportunity to use your quantitative skills in statistics, machine learning and economics, problem solve on high impact open questions, prototype cutting edge mechanisms to production and engage in large scale experimentation and your customer obsession business insight. You will be collaborating closely with Products, Ops, Engineering, and other Data Scientists and Product Analysts to own and drive a large part of the Driver Movement & Pricing data science roadmap and take our products to the next level.
What You'll Do
- Build key algorithms behind real-time pricing, driver movement and driver preferences products;
- Design and analyze experiments that provide insights to improve marketplace efficiency;
- Contribute to the marketplace roadmap through working closely with engineers, product managers and other stakeholders.
- 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
- Ph.D. in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields
- Experience in experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
- Strong experience in causal inference, optimization, and machine learning
- Experience in algorithm development and prototyping.
- Advanced knowledge of experiment design and statistical methods
- Ability to drive clarity on the best modeling or analytic solution for a business objective
- Experience with productionizing algorithms for real-time systems
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.