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NEXTMOVEFDE careers · United States

Senior Applied Scientist - Shipper Pricing

AI summary of the role

Senior Applied Scientist on the Shipper Pricing team, applying ML, causal inference, and optimization to real-time bidding algorithms for freight.

What you’ll do

  • Develop creative algorithms for optimally trading off gross revenue and net revenue when bidding on shipper freight in real time across various auction settings.
  • Prototype and evaluate solutions using statistical analysis and simulation.
  • Collaborate with engineering teams to deploy, experimentally evaluate, and productionize solutions.
  • Leverage data to understand product performance and identify improvement opportunities, including analyzing potential causal factors.

What you’ll bring

  • Ph.D. or M.S. in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact.
  • 4+ years of experience developing and deploying ML models and optimization algorithms in production environments with measurable business impact.
  • Experience designing, executing, and analyzing experiments to measure impact of changes to production ML models.
  • Expertise in observational causal inference or statistical analysis.

Technologies

machine learning · causal inference · optimization · Python · SQL · Spark · reinforcement learning · neural networks · simulation · experimentation

About Uber Freight (acquired Convoy)

Enterprise logistics platform combining TMS software, managed transportation, brokerage capacity and AI agents to run large shippers' freight networks across North America and Europe.

Public · 5000+ people

Source and classification

Internal deployment & tooling · Evidence for this classification:

Schedule: Full Time Employment Job Type: Hybrid Salary Type: Salary Req #: 2537 About the Role As a Sr. Applied Scientist 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 the opportunity to heavily influence 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
More from the job description

Schedule: Full Time Employment Job Type: Hybrid Salary Type: Salary Req #: 2537 About the Role As a Sr. Applied Scientist 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 the opportunity to heavily influence 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 ass [... source excerpt omitted ...] or equivalent technical background with exceptional demonstrated impact 4+ years of experience in developing and deploying machine learning models and optimization algorithms in production environments, delivering measurable business impact over multiple quarters and making significant technical contributions Experience with designing, executing and analyzing experiments to measure the impact of changes to production ML models 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 m [... source excerpt omitted ...] fficiently. 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 www.uberfreight.com. 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. EE

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