Logistics Data Analyst

About the role

Logistics Data Analyst

Newark, NJ $80,000

Overview

A growing organization is seeking a highly analytical and detail-oriented Logistics Data Analyst to serve as the data expert for its Logistics department. This role is responsible for transforming complex operational data into meaningful insights that drive decision-making, improve performance, and provide financial visibility across logistics operations.

The ideal candidate enjoys solving business problems through data, identifying trends and root causes, and communicating findings clearly to both technical and non-technical stakeholders. This position plays a key role in supporting leadership through KPI reporting, dashboard development, operational analysis, and continuous process improvement.

Key Responsibilities

Operational Data & Decision Support

• Produce accurate, timely, and actionable data to support operational and leadership decisions

• Analyze logistics data to identify trends, risks, and opportunities

• Validate operational initiatives and process improvements using performance data

• Distinguish one-time anomalies from recurring operational issues

Financial & P&L Analysis

• Analyze logistics costs, shipment economics, billing trends, and operational expenses

• Identify cost drivers, variances, savings opportunities, and areas of cost leakage

• Support Logistics leadership with P&L visibility and financial reporting

• Partner with Finance to ensure reporting accuracy and data integrity

Reporting & Dashboard Management

• Build, maintain, and improve KPI dashboards and operational scorecards

• Define reporting logic and ensure metrics are clearly understood by stakeholders

• Maintain recurring reports while responding to ad hoc analysis requests

• Update reporting structures as business processes evolve

Project & Performance Analysis

• Perform root-cause analysis for operational challenges and service issues

• Measure project performance before and after implementation

• Develop ROI analyses to support business decisions and process improvements

• Provide data-driven recommendations to improve operational efficiency

Data Quality & Governance

• Ensure logistics reporting is accurate, reliable, and consistent

• Investigate discrepancies across multiple data sources

• Document data definitions, assumptions, and calculation methodologies

• Work with internal stakeholders to resolve data quality issues