Applied Scientist III - Shipper Pricing

About the role

As an Applied Scientist III on the Shipper Pricing team, you will apply machine learning, casual inference and optimization techniques to develop and improve Uber Freight's algorithms for real time bidding on shipper freight. You will have a direct impact on Uber Freight's key business metrics and work closely with senior ICs to shape the technical direction for this area. You will collaborate closely with Product, Operations, Engineering, and other scientists in the department on a daily basis. What the Candidate Will Do Develop creative algorithms for optimally trading off gross revenue and net revenue when bidding on shipper freight in real time across a variety of settings, e.g., open auctions, sealed auctions, reverse waterfall auctions, etc. Prototype and evaluate solutions using statistical analysis and simulation. Collaborate with engineering teams to deploy, experimentally evaluate, and productionize these solutions. Leverage data to understand product performance and identify improvement opportunities, including analyzing potential causal factors. Establish standard methodologies for data science, including modeling, coding, analytics, and experimentation. Communicate findings and insights to senior management and cross-functional teams. Provide recommendations to assist quick product ideation and feature launch decisions.

Requirements

• M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background
• 3+ years of experience in developing and deploying machine learning models and optimization algorithms in production environments
• Proficiency in designing, launching, and analyzing A/B tests or other types of online experiments
• Expertise in observational causal inference or statistical analysis
• Proficiency in Python, SQL and Spark
• Experience developing NN algorithms
• Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• Track record of translating ambiguous business problems into technical solutions
• Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
• Familiarity with reinforcement learning and causal machine learning
• Benefits & Compensation for U.S. Employees
• About Uber Freight
• Candidate Privacy Notice
• Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice .
• EEOC
• For California-based roles: The salary range for this role is $149,500.00 - $182,350.00 per year

Benefits

Additional Information

Schedule: Full Time Employment Job Type: Hybrid Salary Type: Salary Req #:2538

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