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Staff Scientist- UBER Eats Search

3 weeks ago

Hyderabad Telangana, India Uber Full time

**About the Role**

Uber Eats is seeking a highly skilled and motivated Scientist to join our Search Team. As a Scientist, you will play a critical role in enhancing the search experience for millions of Uber Eats users worldwide. You will leverage your expertise in data analysis, machine learning, and statistical modeling to drive insights and optimize search algorithms, ultimately improving user satisfaction and operational efficiency.

**What You'll do**:

- Conduct thorough analyses of large datasets to identify trends, patterns, and opportunities for improving search performance.
- Design, implement, and optimize search algorithms to enhance the relevance and accuracy of search results.
- Mentor and lead junior ICs and make meaningful contributions across various surfaces of Search
- 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 search technologies.
- Define how our teams measure success, by developing metrics, in close partnership with cross functional partners.

**What You'll need**:

- M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- 10+ years of industry experience as an Applied or Data Scientist or equivalent.
- Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn),
- 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
- Experience in developing causal inference methodologies and experimental design (e.g., A/B and market-level experiments)
- Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.