Logistics Data Analyst

Job Description

Position Summary The Logistics Data Analyst owns the data foundation that supports operational decision-making across the Logistics Department. This role produces fast, reliable, and explainable data for leadership decisions, P&L visibility, KPI tracking, dashboard reporting, project validation, and operational scorecards. The analyst turns raw and messy logistics data into usable insights, validates whether ideas and process changes are supported by actual data, investigates data discrepancies, and helps ensure Logistics reporting remains accurate, trusted, and actionable. Why This Role Exists Logistics does not make important operational decisions without data supporting it. P&L visibility requires clean, traceable, and explainable logistics data. Operations require accurate KPIs, dashboards, scorecards, and fast one-time analysis requests. Projects and process changes need data validation before they move forward and performance tracking after launch. Data integrity must be high enough that when a number is questioned, the source, logic, and issue can be clearly explained.

Key Responsibilities

• Decision-Ready Data Support
• Produce fast, reliable, and explainable data to support leadership and operational decisions.
• Translate operational questions into clear data pulls, analysis, findings, and recommended next steps.
• Validate whether proposed ideas, process changes, or improvement opportunities are supported by volume, cost, service, or performance data.
• Separate one-off noise from recurring operational patterns that require action.
• P&L and Cost Visibility
• Support Logistics P&L visibility by analyzing cost drivers, shipment economics, billing trends, variance patterns, and financial impact of operational changes.
• Build and maintain analysis that helps explain actual vs. expected cost behavior, cost leakage, savings opportunities, and department-level financial performance.
• Partner with leadership and Finance as needed to ensure logistics data is accurate, traceable, and usable for decision-making.
• KPI, Dashboard, and Scorecard Ownership
• Build, maintain, and improve operational dashboards, KPI reports, and department scorecards based on business need.
• Define KPI logic clearly so users understand what each metric means, where it comes from, and how it should be used.
• Monitor dashboard reliability and update reporting logic when workflows, systems, or business rules change.
• Support recurring reporting as well as urgent one-time pull requests.
• Project and Issue Analysis
• Provide data-driven recommendations for logistics projects, operational issues, and process improvement initiatives.
• Perform root-cause analysis to identify what is driving performance issues, cost increases, service failures
• Measure pre-launch baselines and post-launch results to confirm whether a project or fix delivered the expected impact.
• Create practical ROI and impact models helping decide if to proceed, pause, modify, or drop an initiative.
• Data Integrity and Explainability
• Own data accuracy, consistency, and reliability for Logistics reporting and analysis.
• Investigate when numbers look incorrect, sources conflict, or reporting logic is unclear.
• Document data definitions, assumptions, calculation logic, limitations, and known issues.
• Work with Tech, systems owners, or other stakeholders to correct or escalate data quality issues when they affect decision-making.
• Cross-Functional Communication
• Communicate findings clearly to technical and non-technical stakeholders.
• Turn complex analysis into simple, practical summaries that explain what matters, why it matters, and what action should be considered.
• Collaborate with Logistics Office, Warehouse, Tech, Finance, and other departments to understand data needs and deliver analysis aligned with operational priorities.
• Required Qualifications
• Strong analytical ability with experience collecting, cleaning, organizing, and interpreting operational or financial data.
• Advanced Excel skills and comfort working with large data sets.
• Experience with reporting, dashboarding, or BI tools such as Power BI, Tableau, ThoughtSpot, SQL-based reports, or similar platforms.
• Ability to explain data logic clearly in plain business language.
• Strong attention to detail and accuracy, especially when data is used for financial or operational decisions.
• Ability to work with cross-functional stakeholders and clarify the real business question behind a data request.
• Strong follow-through and ability to handle recurring reports, urgent requests, and project-based analysis without losing track of details.
• Experience investigating data discrepancies across multiple systems.

Preferred Qualifications

• Experience in logistics, supply chain, transportation, warehouse operations, or manufacturing environments.
• Working knowledge of TMS, WMS, ERP, shipping, routing, carrier, billing, or order-management data.
• SQL or database-query experience.