Scientist II - Reservations

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 You Will Do

• Deploy a wide variety of methodologies, including causal inference techniques, experiments, funnel analyses, ML modeling and Optimization algorithms to solve real world business and customer problems.
• Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy
• Present findings to technical and non-technical audiences.
  
  

Basic Qualifications

• 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.
  
  

Preferred Qualifications

• Ability to drive clarity on the best modeling or analytic solution for a business objective
• Experience in building statistical, optimization, and machine learning models for a range of applications.
• 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
  
  

For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits., For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.