Key Responsibilities and Required Skills for Cargo Supply Chain Analyst

🎯 Role Definition

The Cargo Supply Chain Analyst analyzes freight flows, capacity and cost drivers across multimodal cargo networks, identifying improvement opportunities and implementing process and system changes that reduce cost, improve on-time performance and increase cargo revenue. This role blends quantitative analysis (modeling, forecasting, KPI tracking) with operational execution (route optimization, carrier performance, tendering and S&OP support) and requires strong stakeholder management, systems literacy and practical logistics experience.

📈 Career Progression

Typical Career Path

Entry Point From:

Logistics Coordinator or Cargo Operations Specialist with strong analytical aptitude
Data Analyst or Business Analyst embedded in transportation or logistics teams
Freight Pricing Analyst, Revenue Management Analyst, or Capacity Planner

Advancement To:

Senior Cargo Supply Chain Analyst / Lead Analyst
Supply Chain Optimization Manager or Capacity Planning Manager
Global Logistics Manager or Network Planning Manager

Lateral Moves:

Commercial Analytics (pricing & yield management)
Operations Excellence / Continuous Improvement
Data Engineering or BI Product Owner for logistics platforms

Core Responsibilities

Primary Functions

Conduct end-to-end analysis of cargo flows (air, ocean, and ground) including origin-destination volumes, transit times, capacity utilization and throughput to identify bottlenecks and cost-saving opportunities.
Build, maintain and validate forecasting models for cargo demand, capacity requirements and seasonal trends leveraging time-series methods, causal models and scenario analysis to support procurement and network planning.
Develop and track key performance indicators (KPIs) such as on-time performance, dwell time, yield per kg, cost-per-tonne-km and capacity utilization; produce weekly/monthly dashboards and executive summaries for stakeholders.
Lead route and network optimization projects by evaluating lane performance, capacity options, and routing alternatives to reduce transit time and operating cost while protecting service levels.
Conduct landed-cost and cost-to-serve analyses for major cargo lanes and customer segments, identifying components of freight cost (fuel, handling, duty, surcharges) and recommending tactical and strategic changes.
Partner with commercial teams to supply data-driven inputs for pricing negotiations, tender responses and carrier selection, including benchmarking carrier performance and total cost comparisons.
Design and execute freight procurement strategies and RFP processes, modeling scenarios, evaluating carrier proposals and documenting trade-offs between cost, capacity and service commitments.
Perform root-cause analysis for operational disruptions (e.g., capacity shortages, service irregularities, customs delays) and coordinate corrective actions with operations, carriers and customs brokers to restore service.
Translate business requirements into technical specifications and partner with IT/BI teams to deliver reports, dashboards and analytics features in data warehouses and visualization tools (e.g., Tableau, Power BI, Looker).
Maintain and enrich cargo master data (product codes, commodity classifications, route attributes, tariffs) and ensure data quality across TMS, WMS and ERP systems to enable accurate analytics and reporting.
Automate repeatable analytics workflows using SQL, Python or R, reducing manual effort and increasing speed of insight delivery for commercial and operations teams.
Design and run A/B tests and pilot programs (e.g., new routing rules, capacity pools, packaging changes) and measure impact on cost, performance and customer satisfaction.
Support S&OP and Integrated Business Planning processes by providing demand vs. capacity reconciliations, inventory visibility and proactive escalation of constraints.
Evaluate and recommend technology solutions (TMS modules, capacity management platforms, optimization engines) and participate in vendor assessments, pilots and implementations.
Monitor regulatory and market changes (tariffs, trade lanes disruptions, fuel price volatility) and quantify potential impacts on cargo supply chain cost and capacity.
Develop and deliver training and user guides to enable business users to interpret analytics, use dashboards and follow best practices for data entry and workflow.
Create executive-level presentations and business cases to secure funding for supply chain improvements, demonstrating quantified ROI, implementation roadmap and risk mitigation.
Collaborate with customs compliance, freight forwarding and trade operations to streamline documentation flows and reduce clearance times and penalties.
Maintain strong relationships with carriers, ground handling agents and 3PL partners; monitor vendor SLAs and performance metrics, and lead service improvement initiatives when KPIs fall below targets.
Implement and monitor capacity contingency plans and surge management playbooks during peak seasons, disruptions or schedule changes to maintain cargo throughput and customer commitments.
Conduct customer segmentation analysis and route profitability reviews to recommend tailored service offerings, contract terms and value-based pricing strategies.
Integrate external datasets (market capacity feeds, port/airport congestion data, commodity price indices) with internal data to enrich models and improve forecasting and decision-making accuracy.
Ensure compliance with company policies and industry regulations (e.g., hazardous materials handling, export controls) by incorporating regulatory constraints into planning and operating procedures.
Drive continuous improvement initiatives using Lean/Six Sigma methods to simplify processes, eliminate waste and reduce cycle times across cargo supply chain operations.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.

Required Skills & Competencies

Hard Skills (Technical)

Advanced SQL for data extraction, transformation and analysis across large logistics datasets.
Proficiency in Python or R for statistical modeling, time-series forecasting and automation of analytics workflows.
Experience with business intelligence and visualization tools (Tableau, Power BI, Looker) to build interactive dashboards and management reports.
Familiarity with Transportation Management Systems (TMS), Warehouse Management Systems (WMS) and ERP integrations; experience with major cargo platforms is a plus.
Strong quantitative modeling skills: capacity planning, route optimization, linear programming or mixed-integer programming experience is advantageous.
Competence in forecasting techniques: ARIMA, exponential smoothing, causal models and scenario planning.
Knowledge of freight costing methodologies, landed cost calculations and yield/cost-per-unit economics.
Experience with data engineering concepts, data warehousing (Snowflake, Redshift, BigQuery) and ETL processes.
Understanding of customs, trade compliance and cargo documentation requirements across air and ocean freight.
Ability to perform SQL-based data validation and establish data quality checks and monitoring.
Familiarity with GIS or geospatial tools for route and hub analysis is beneficial.
Experience using optimization or supply chain planning software (e.g., Gurobi, CPLEX, AIMMS) or advanced Excel solver models.

Soft Skills

Strong stakeholder management and influencing skills to align commercial, operations and IT teams.
Excellent written and verbal communication; able to translate technical analysis into business recommendations and executive presentations.
Problem-solving mindset with attention to detail and an ability to prioritize trade-offs under uncertainty.
Project management capability to lead cross-functional initiatives from problem definition through deployment.
Adaptability and resilience in fast-moving logistics environments with changing priorities and peak season challenges.
Collaborative team player who can work across global teams and time zones.
Customer-centric orientation, balancing operational efficiency with service reliability and customer commitments.
Analytical curiosity and continuous improvement orientation; comfortable experimenting and iterating on models and processes.
Ethical decision-making and strong sense of data governance and confidentiality.
Coaching and mentoring skills to grow junior analysts and train business users on analytics tools.

Education & Experience

Educational Background

Minimum Education:

Bachelor’s degree in Supply Chain Management, Logistics, Industrial Engineering, Operations Research, Data Science, Economics, Business Analytics, or related field.

Preferred Education:

Master’s degree (MS in Supply Chain Management, MBA with supply chain concentration, MSc in Analytics) or relevant professional certifications (APICS/CPIM, CSCP, Lean Six Sigma, or IATA cargo certifications).

Relevant Fields of Study:

Supply Chain Management / Logistics
Industrial Engineering / Operations Research
Data Science / Analytics
Business Administration / Economics

Experience Requirements

Typical Experience Range: 3–7 years of relevant experience in cargo operations, freight forwarding, airline/shipper cargo planning, or logistics analytics.

Preferred:

5+ years working in cargo supply chain roles with direct exposure to network planning, capacity procurement, or freight analytics.
Demonstrated experience building forecasting and optimization models, leading cross-functional projects, and presenting to senior stakeholders.
Prior experience with multimodal freight (air, ocean, road) and familiarity with global trade flows and regulatory requirements.