Uber's Rider team is looking to innovate on ranking algorithms and tackle challenges in simulation/forecasting, LLM applications, and reinforcement learning to enhance the ranking experience for millions of Rider app users worldwide, ultimately improving user satisfaction and achieving business growth.
Requirements
- Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn),
- Experience in large-scale experiment design (e.g., A/B and market-level experiments)
- Prior experience with feed ranking or search algorithms
- Solid understanding of MLOps practices, including design documentation, testing, and source code management with Git.
- Advanced skills in the development and deployment of large-scale ML models and optimization algorithms
Responsibilities
- Conduct thorough analyses of large datasets to identify trends, patterns, and opportunities for improving ranking performance.
- Design, implement, and optimize ranking algorithms to enhance the relevance and accuracy of ranking results.
- Generate actionable insights from data and communicate findings to stakeholders across the organization.
- Design experiments and interpret the results to draw detailed and impactful conclusions.
- Work closely with product managers, engineers, and other scientists to define project goals and deliver data-driven solutions.
- Stay current with the latest advancements in data science, machine learning, and feed ranking technologies.
- Define how our teams measure success, by developing metrics, in close partnership with cross-functional partners.
Other
- Mentor and lead junior ICs and make meaningful contributions across various surfaces of the Rider app
- Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.
- M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- 5+ years of industry experience as an Applied or Data Scientist or equivalent.
