Applied Scientist III

About the role

The position invites you to join the Shipper Pricing team where your primary focus will be the construction and enhancement of real-time bidding algorithms within the complex world of freight logistics. You will be responsible for directly influencing core business outcomes by applying a robust toolkit that includes machine learning, causal inference, and mathematical optimization techniques. In this capacity, you will work in close collaboration with senior staff members and a wide array of cross-functional partners to ensure technical solutions align with overarching business goals. The role requires you to navigate the intersection of data science and commercial reality, translating ambiguous logistical constraints into precise mathematical formulations. You will be expected to maintain a high standard of technical rigor while ensuring that your models remain interpretable and actionable for stakeholders. Success in this role will be measured by your ability to improve auction efficiency and drive sustainable revenue growth in a dynamic market environment. You will serve as a technical leader, guiding the direction of algorithmic development from initial concept through to production deployment and ongoing refinement.

Key facts

Location: USA

Engagement: Full-time, Hybrid

Salary: $124,600.00 - $151,950.00 per year

Req #: 2538

Team: Shipper Pricing

What you'll do

• Design algorithms to balance gross and net revenue during real-time bidding across various auction formats.
• Use simulations and statistical methods to prototype and validate new solutions before they touch live systems.
• Partner with engineering squads to deploy models into production environments and run rigorous experimental evaluations.
• Use data to identify product performance trends and analyze causal factors for improvement using advanced statistical techniques.
• Define best practices for modeling, coding standards, and experimentation protocols to ensure consistency across the team.
• Present technical findings and recommendations to leadership stakeholders to guide strategic product decisions and roadmaps.
• Develop a deep understanding of the freight marketplace dynamics to inform the feature engineering process for predictive models.
• Conduct rigorous error analysis to diagnose model failures and iterate on improvements based on empirical evidence.
• Collaborate with data engineers to ensure data quality, accessibility, and pipeline reliability for model training and inference.
• Explore novel algorithmic approaches to maximize win rates while maintaining healthy profit margins for the business.

Requirements

• Hold a Bachelor or Master degree in Computer Science, Machine Learning, Operations Research, or a related technical field that provides a strong theoretical foundation.
• Bring 3+ years of professional experience building and deploying machine learning and optimization models in production environments with measurable impact.
• Demonstrate a proven ability to design and analyze A/B tests and online experiments to measure the true impact of algorithmic changes.
• Show expertise in statistical analysis and observational causal inference to isolate the effect of interventions in complex real-world settings.
• Exhibit proficiency in Python, SQL, and Spark to manipulate large datasets and build scalable computational pipelines.
• Possess strong analytical and problem-solving skills to deconstruct complex business problems into solvable technical components.
• Have experience working with high-dimensional datasets and performing feature selection to improve model generalization.
• Display a commitment to writing clean, maintainable code that adheres to software engineering best practices and version control workflows.

Nice to have

• Possess experience with neural network algorithms and deep learning frameworks to tackle complex pattern recognition tasks.
• Have a background in pricing for multi-sided, real-time marketplaces involving strategic agents and complex game-theoretic considerations.
• Show an ability to turn vague business challenges into concrete technical plans with clearly defined success metrics and milestones.
• Demonstrate familiarity with reinforcement learning and causal machine learning to build adaptive and intelligent systems.
• Maintain strong communication skills for cross-functional collaboration, enabling effective translation between technical and non-technical audiences.

Practical notes

This role is based in Chicago, Illinois, and requires a hybrid work arrangement that combines office presence with remote flexibility. The compensation package for this position ranges from $124,600.00 to $151,950.00 on an annual basis, reflecting the level of responsibility and expertise required. Employees in this role may also be eligible for performance or sales bonuses and equity awards as part of their total compensation. Benefits include a company-sponsored health plan, dental and vision coverage, 401k matching, mental and financial wellness programs, parental leave, life insurance, and disability coverage. Uber Freight is an Equal Opportunity/Affirmative Action employer, and the company adheres to strict guidelines regarding the handling of candidate data as outlined in the candidate privacy notice. This is a full-time position that requires a hybrid schedule, and successful candidates must be authorized to work in the United States without sponsorship for this role at this time.