What are the responsibilities and job description for the Scientist II - Reservations position at Uber?
About The Role
The Reserve product is a maturing product, most of the low hanging fruit" initiatives to improve the experience to consistently deliver high reliability have been delivered. Currently, our focus is in building smart levers to maintain reliability while driving efficiency, improving our unit economics and growing adoption and retention.
Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth.
What The Candidate Will Need / Bonus Points
What the Candidate Will Do
The Reserve product is a maturing product, most of the low hanging fruit" initiatives to improve the experience to consistently deliver high reliability have been delivered. Currently, our focus is in building smart levers to maintain reliability while driving efficiency, improving our unit economics and growing adoption and retention.
Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth.
What The Candidate Will Need / Bonus Points
What the Candidate Will Do
- Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy
- Run large scale experiments, observational studies, deep dives into business and user behavior trends and present findings to technical and non-technical audiences
- Ph.D., M.S. or Bachelor's degree in Statistics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- 2 years of industry experience as an Applied or Data Scientist or equivalent (not required with Ph.D.).
- Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), underpinned by a solid grasp of MLOps practices, including design documentation, testing, and source code management with Git.
- Good understanding of experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
- Good business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
- Ability to drive clarity on the best analytic solution for a business objective
- Expertise in causal inference, A/B testing designs, multivariate testing, and other advanced analytical methods.
- Experience in designing highly scalable, resilient systems for customer-facing applications and familiarity with optimization techniques.
- Propose, design, and analyze large scale online experiments and interpret the results to draw detailed and actionable conclusions.
- Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization
Salary : $161,000 - $179,000