Senior Scientist, Rider Personalization

Senior Scientist, Rider Personalization Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** The Rider team is the centerpiece of the Uber consumer experience, owning the core flagship app used by over 100M+ monthly active users. The Personalization team is looking for a Senior Scientist who can help us innovate on our AIML efforts  and tackle the next frontier of challenges, including ranking & recommender systems, and agentic applications. As a Scientist, you will play a critical role in enhancing the personalization AIML experience for millions of Rider app users worldwide. You will leverage your expertise in machine learning and data science to optimize our ranking & recommendation systems, help develop agentic applications, and simulate marketplace outcomes, ultimately improving user satisfaction and achieving business growth through one of the most impactful channels. **What You'll Do** - Prototype new models and methodologies (e.g. evidential deep learning, reinforcement learning, listwise ranking) for improving performance across the various personalization AI/ML surfaces of the rider app. - Deep dive the data and optimize current ranking algorithms to enhance the relevance and accuracy of ranking results. - Design experiments and offline simulations to measure the performance of AIML systems, including agentic applications, interpret the results, and make impactful recommendations for areas of development - 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 personalization AIML - Mentor and review the work of junior team members **Basic Qualifications** - M.S. or Bachelor's degree in Computer Science, Statistics, Economics, Mathematics, Operations Research, or other quantitative fields. - 5+ years of industry experience as an Applied Scientist, Research Scientist, or equivalent. - Proficiency in programming languages (Python, PySpark, SQL) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), - Strong