Senior Manager, Logistics Analytics & Optimization

Uber Freight•San Francisco, CA

7d•$143,150 - $196,000•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 of advanced technical teams, evaluating and achieving commercial business objectives through rigorous analysis, modeling, and collaboration. It sits at the intersection of commercial strategy, advanced analytics, and operational execution, with responsibility for analytics outcomes, automation, and overarching results. The manager leads advanced professional-level engineers and works with data scientists to turn interconnected business dynamics into scalable, automated solutions, partnering with Product, Operations, Data Science, and Leadership to improve network efficiency, service, and profitability. The role sets direction for network optimization and analytics initiatives, including freight routing, capacity utilization, cost structures, continuous moves, dedicated fleets, loop-based networks, and specialized routing strategies. It provides commercial decision support across 3PL and 4PL businesses, creates data-backed recommendations, and translates complex freight economics and analytics into executive narratives. The manager also establishes team priorities, allocates resources, manages team costs and staffing, and ensures analytical decision models are adopted in operational workflows and software systems. The position leads governance, documentation, and continuous improvement across analytics models, pipelines, tools, and decision products. It defines adoption KPIs and feedback loops, and directs refinement of products to support end-user adoption and measurable business value. The role conducts and oversees analysis using SQL, Python, Excel, and GCP tools; builds repeatable analytical frameworks; works with large datasets, databases, and ETL pipelines; and develops dashboards and operational reporting using Tableau, Power BI, or similar tools.

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 in 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 acumen across 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.
Excellent 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.
Ability to produce executive reporting and visualizations that make analytical outputs clear, intuitive, and actionable.

Nice To Haves

Experience with VBA or legacy analytical tools.
Hands-on Python experience for data analysis and modeling.
Experience working within the Google Cloud Platform (GCP) ecosystem.
Practical experience applying agentic frameworks, such as tool-calling or semantic layers, to automate 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 constructive feedback and individualized growth opportunities; foster resilience, adaptability, trust, diversity, and inclusion.
Evaluate commercial objectives and leadership requests to define roadmaps for analytics projects involving freight routing optimization, capacity utilization, and transportation-network cost structures.
Integrate data across sources and disciplines to support decisions involving cost, capacity, operational constraints, and service-level trade-offs using optimization techniques.
Direct the design of automated analytics frameworks and implement procedures that can scale across the organization.
Identify network inefficiencies and design solutions to improve margin, service reliability, and scalability.
Support initiatives involving continuous moves, dedicated fleets, loop-based networks, and specialized routing strategies.
Partner with commercial leadership to deliver scenario analyses and data-backed recommendations, owning analytical decision support across 3PL and 4PL businesses.
Promote collaboration among Product, Sales, Operations, and Analytics teams, and help ensure decision models are adopted in frontline workflows and software systems.
Apply an understanding of interconnected business dynamics so technical solutions translate into margin improvement and account retention.
Establish team-wide prioritization and resource-allocation frameworks, balance commercial escalations with long-term modeling roadmaps, and manage team costs, headcount, and project commitments.
Translate freight economics, optimization outputs, and econometric analyses into executive narratives that guide C-suite decisions, align cross-functional leaders, and resolve stakeholder friction.
Establish governance frameworks and documentation standards so models, data pipelines, and analytical tools are transparent, auditable, and resilient to personnel changes.
Implement procedures, analytical toolsets, and optimization methodologies that support continuous learning.
Define adoption KPIs and operational feedback loops, and direct iterative refinement of 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 reports using Tableau, Power BI, or similar BI tools.

Benefits

Company-sponsored health plan for eligible U.S. employees working more than 30 hours per week.
Dental benefits.
Vision benefits.
401(k) match.
Financial and mental wellness benefits.
Parental leave.
Short- and long-term disability coverage.
Life insurance.
Eligible U.S.-based employees may be eligible for a performance or sales incentive bonus program.
Eligible employees may participate in Uber Freight equity awards.
Other types of compensation may be offered depending on the role.