Staff Scientist- Uber Eats Search

10 - 14 years

0 Lacs

Posted:5 days ago| Platform: Shine logo

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On-site

Job Type

Full Time

Job Description

As a Scientist at Uber Eats, you will play a crucial role in the Search Team, dedicated to enhancing the search experience for millions of users across the globe. Your expertise in data analysis, machine learning, and statistical modeling will be instrumental in improving search algorithms, thereby increasing user satisfaction and operational efficiency. Key Responsibilities: - Conduct in-depth analyses of extensive datasets to uncover trends, patterns, and opportunities for enhancing search performance. - Develop, implement, and optimize search algorithms to elevate the relevance and precision of search results. - Guide and supervise junior ICs, contributing significantly to various aspects of Search. - Extract actionable insights from data and communicate findings effectively to stakeholders. - Design experiments, interpret outcomes, and draw detailed conclusions to steer decision-making processes. - Work closely with product managers, engineers, and fellow scientists to establish project objectives and deliver data-driven solutions. - Keep abreast of the latest advancements in data science, machine learning, and search technologies. - Establish success metrics for teams by formulating pertinent metrics in partnership with cross-functional collaborators. Qualifications Required: - Possession of an M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or related quantitative fields. - A minimum of 10 years of industry experience as an Applied or Data Scientist or in an equivalent role. - Proficiency in programming languages like Python, Java, Scala, and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. - Thorough understanding of MLOps practices, encompassing design documentation, testing, and source code management utilizing Git. - Advanced capabilities in developing and deploying large-scale ML models and optimization algorithms. - Hands-on experience in creating causal inference methodologies and experimental design, including A/B and market-level experiments. - Business acumen and product sense to translate ambiguous inquiries into well-defined analyses and success metrics that steer business decisions.,

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Uber

Technology, Information and Internet

San Francisco California

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