Applied Scientist III - Shipper Pricing

Schedule: Full Time Employment

Job Type: Hybrid

Salary Type: Salary

Req #:2538

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.

Basic Qualifications

• 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

Preferred Qualifications

• 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

Employees working more than 30 hours in the US at Uber Freight are eligible for benefits like a company sponsored health plan, dental and vision benefits, 401k match, financial and mental wellness benefits, parental leave, short- and long-term disability coverage, life insurance and more. US based employees may also be eligible for a performance or sales incentive bonus program, participation in Uber Freight equity awards, and other types of compensation depending upon the role.

About Uber Freight

Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using real‑time data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at .

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

Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.