Uber Staff Machine Learning Engineer - Driver Incentives 

United States, West Virginia 

615103203

What You Will Do

• Build statistical, optimization, and machine learning models for applications including pricing, targeting, and experimentation.
• Work with engineers and product managers to turn data science prototypes into robust, reliable machine learning (ML) solutions.
• Use data to understand product performance and to identify improvement opportunities.
• Solve ambiguous, challenging business problems using data-driven approaches.
• Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
• Develop new methodologies for data science including modeling, coding, analytics, optimization, and experimentation.
• Collaborate with cross-functional teams such as product, operations, and marketing to drive system development end-to-end from conceptualization to final product.

Basic Qualifications

• Ph.D. or M.S. in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
• 6+ years of industry experience in machine learning, including building and deploying ML models at scale.
• Experience in modern deep learning architectures and probabilistic modeling
• 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
• Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.

Preferred Qualifications

• Expertise in developing causal inference methodologies, experimental designs, and advanced analytical methods.
• Strong experience in building a wide range of models (e.g. causal inference, optimization, ML) for business applications.
• Experience in algorithm development and rapid prototyping.
• Design, develop, and operationalize econometric models to assess challenging causal problems such as product incrementality and long-term value
• Propose, design, and analyze large scale online experiments and interpret the results to draw actionable conclusions.
• Ability to drive clarity on the best modeling solution for a business objective
• Collaborate with cross-functional teams across disciplines such as product, engineering, and operations to drive system development end-to-end from generating ideas to productionizing.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.