10.0 - 14.0 years

0 Lacs

karnataka

On-site

As a Staff Data Scientist at Uber Eats, you will play a crucial role in enhancing the search experience for millions of users worldwide. Your deep statistical expertise will drive decision-making, improve product performance, and ensure that our evaluations and insights are based on methodological rigor. Your responsibilities will include conducting robust statistical analyses on complex datasets to identify product opportunities, shape roadmap priorities, and optimize user experiences in search. You will design and evaluate A/B tests and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights. Building and maintaining statistical frameworks for defining and measuring ground truth will be a key aspect of your role, to identify reliable signals for evaluating search relevance, personalization, and user satisfaction. You will apply advanced sampling strategies to construct representative datasets for both offline and online evaluation pipelines, ensuring scalability and statistical power. Developing rigorous evaluation metrics that reflect real-world product performance and align closely with user and business goals will be essential. Additionally, you will lead initiatives to enhance causal inference practices across the team, applying methods like matching, regression discontinuity, and difference-in-differences where appropriate. Collaborating with product managers, engineers, and other scientists, you will translate open-ended product questions into structured analytical approaches. Providing mentorship and technical leadership to other scientists, you will promote a culture of statistical excellence and continuous learning within the team. To excel in this role, you should have an M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Operations Research, Computer Science, or a related quantitative field. With 10+ years of industry experience in data science or applied analytics, ideally in consumer products, search, or recommendation systems, you should possess deep expertise in ground truth design and evaluation methodologies for complex user-facing systems. Your proven experience with statistical sampling techniques, offline evaluation pipelines, experimentation design, causal inference, and observational data analysis will be valuable. Proficiency in tools like SQL, Python, and R for data manipulation, modeling, and visualization is required. Excellent communication skills are essential, as you will need to present statistical findings clearly and influence product and engineering decisions through data. Having a strong product sense and the ability to balance analytical rigor with practical business impact will be advantageous in this role.,

Posted 1 day ago

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