Senior Manager, Logistics Analytics & Optimization

Uber Freight•Chicago, IL

11d•Hybrid

About The Position

Uber Freight is seeking a Senior Manager, Logistics Analytics & Optimization to lead the design, analytics, and optimization of complex freight networks at scale. The role is a strategic owner responsible for managing advanced technical teams, evaluating commercial objectives, and supporting strategic decisions through rigorous analysis, modeling, and collaboration. It combines commercial strategy, advanced analytics, and operational execution, with accountability for analytics outcomes and automation. The Senior Manager will lead advanced professional-level engineers and collaborate with data scientists, translating interconnected business dynamics into scalable, automated solutions. The position partners closely with Product, Operations, Data Science, commercial leadership, and other leaders to improve network efficiency, service, and profitability across Uber Freight's 3PL and 4PL businesses. The role oversees freight routing and network optimization, capacity utilization, cost structures, scenario analysis, and decision-support models. It also establishes team priorities, governance and documentation standards, adoption measures, and continuous-improvement processes. The manager conducts and guides technical analysis using SQL, Python, Excel, GCP tools, large datasets, ETL pipelines, and BI tools, and communicates complex analytical findings through executive-ready narratives and visualizations. The position is full time and hybrid. For Illinois-based employees, the base salary range is $119,300–$161,000. U.S. employees working more than 30 hours are eligible for a range of benefits; employees may also be eligible for incentive compensation and equity awards depending on role.

Requirements

At least 8 years of experience in logistics, transportation, freight brokerage, or supply-chain network design.
At least 3 years of direct experience managing advanced analytical or engineering teams.
Advanced proficiency in SQL and Excel, including complex formulas and scenario modeling.
Familiarity with databases, ETL workflows, and large-scale operational datasets.
Experience building dashboards and operational metrics in Tableau, Power BI, or similar tools.
A proven track record of managing costs, overseeing staffing, and achieving upper-level strategic results.
Deep expertise in operations research, network optimization, and commercial freight economics.
Expertise with optimization methodologies related to routing, capacity planning, and service-level trade-offs.
Experience or familiarity guiding data science or analytics teams in deploying AI-powered decision-support tools, conversational analytics, or automated diagnostic workflows.
Deep commercial understanding of freight market cycles, contract versus spot dynamics, carrier procurement, logistics network sensitivities, and margin elasticity.
Ability to structure ambiguous network-design problems and direct teams in formulating optimization, simulation, and predictive models.
Strong organizational and prioritization skills in ambiguous, fast-paced environments.
High-impact communication and executive presence, including the ability to negotiate cross-functional priorities, coach technical talent, and align commercial and engineering perspectives.

Nice To Haves

Experience with VBA or legacy analytical tools.
Hands-on experience with Python for data analysis and modeling.
Experience working within the Google Cloud Platform ecosystem.
Practical experience applying agentic frameworks, such as tool-calling and semantic layers, to automate routine commercial reporting and root-cause analysis over transportation datasets.

Responsibilities

Manage a team of advanced technical professionals, set expectations and KPIs, delegate work, and support team productivity and goal achievement.
Coach and develop team members through regular feedback and individualized growth opportunities; foster resilience, adaptability, trust, diversity, and inclusion.
Evaluate commercial objectives and leadership requests to define analytics project roadmaps for freight routing optimization, capacity utilization, and network cost structures.
Integrate data from multiple sources to analyze cost, capacity, operational constraints, and service-level trade-offs using optimization techniques.
Direct the design of automated analytics frameworks and implement procedures that scale across the organization.
Identify network inefficiencies and design solutions to improve margin, service reliability, and scalability.
Support continuous-move, dedicated-fleet, loop-based network, and specialized-routing initiatives.
Partner with commercial leadership on scenario analysis and data-backed recommendations, owning analytical decision support across 3PL and 4PL businesses.
Promote collaboration among Product, Sales, Operations, Analytics, and other departments, and ensure decision models are adopted in frontline workflows and software systems.
Connect technical solutions to margin improvement and account retention by considering how business dynamics are interconnected.
Establish team prioritization and resource-allocation frameworks that balance commercial escalations with longer-term modeling roadmaps, team costs, headcount, and delivery commitments.
Translate freight economics, optimization outputs, and econometric analyses into executive narratives that support C-suite decisions and cross-functional alignment.
Establish governance frameworks and documentation standards so network models, data pipelines, and analytical tools are transparent, auditable, and resilient to personnel changes.
Implement procedures, analytical tools, and optimization methodologies that support continuous learning.
Define adoption KPIs and operational feedback loops, and direct iterative improvements to decision products to increase adoption and measurable business value.
Conduct deep-dive analyses using SQL, Python, advanced Excel formulas, and GCP tools to support engineering and business decisions.
Build and maintain repeatable analytical frameworks for network evaluation and performance monitoring.
Work with large-scale datasets, databases, and ETL pipelines in fast-moving operational environments.
Develop dashboards, KPIs, and operational reporting using Tableau, Power BI, or similar tools.
Set standards for executive reporting and visualization so analytical outputs are clear, intuitive, and actionable.