Senior Manager, Logistics Analytics & Optimization

Uber Freight•Seattle, WA

11d•$131,250 - $178,000•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 accountability for results, analytics outcomes, and automation. The position leads advanced professional-level engineers and collaborates with data scientists, translating interconnected business dynamics into scalable, automated solutions. It partners closely with Product, Operations, Data Science, and Leadership to improve network efficiency, service, and profitability across Uber Freight. The role directs analytics roadmaps and decision support for freight routing, capacity utilization, cost structures, and network optimization across 3PL and 4PL businesses. It develops automated analytical frameworks, supports commercial and operational decisions, and establishes governance, documentation, prioritization, adoption measurement, and continuous-improvement practices. The role also conducts and guides technical analysis using SQL, Python, Excel, GCP tools, large-scale datasets, ETL pipelines, and BI tools.

Requirements

At least 8 years of experience in logistics, transportation, freight brokerage, or supply chain network design.
At least 3 years of experience directly 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.
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.
Strong communication and executive presence, including negotiating cross-functional priorities, coaching technical talent, and aligning commercial and engineering perspectives.
Ability to produce clear executive reporting and visualizations that make analytical outputs intuitive and actionable.

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 (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, provide feedback, and support individualized professional growth.
Build a resilient, inclusive team culture and help team members navigate uncertainty and operational change.
Define roadmaps for analytics projects addressing freight routing optimization, capacity utilization, cost structures, and complex transportation networks.
Integrate data across sources and disciplines to assess cost, capacity, operational constraints, and service-level trade-offs using optimization techniques.
Direct the design of automated analytics frameworks and implement scalable procedures across the organization.
Identify network inefficiencies and design solutions that 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 analysis and data-backed recommendations, owning analytical decision support across 3PL and 4PL businesses.
Promote collaboration across Product, Sales, Operations, and Analytics teams, ensuring decision models are adopted into frontline workflows and software systems.
Connect technical solutions to margin improvement and account retention through analysis of interconnected business issues.
Establish team prioritization and resource-allocation frameworks, balancing urgent commercial requests with long-term modeling roadmaps and managing costs, headcount, and delivery commitments.
Translate freight economics, optimization outputs, and econometric analyses into executive narratives that guide C-suite decisions and align cross-functional leaders.
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 improve 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 BI tools.