Industrial Engineer - Planning & Analytics

Job Description

Job Description

Description:

Position Summary

The Industrial Engineer – Planning & Analytics is responsible for using operational data, industrial engineering principles, and analytical tools to improve efficiency, capacity planning, service performance, and operating cost across RAS Logistics' network.

This role partners closely with Operations leadership, including division and VP-level leaders, as well as site management, to identify performance gaps, improve processes, develop forecasting and staffing models, and establish consistent operating standards.

A key focus of this position is translating operational volume into actionable capacity and driver/team requirements. The Industrial Engineer will develop forecasting tools that help locations determine the appropriate level and mix of delivery capacity while improving route utilization and reducing unnecessary operating costs.

The role will also support work measurement, process improvement, driver-pay analysis, and bid profitability to help ensure operational decisions support both service expectations and financial performance.

Essential Duties & Responsibilities

• Develop, maintain, and enhance operational dashboards that provide leadership with visibility into productivity, service performance, cost, capacity, and other key operational metrics.
• Build reporting tools and internal applications using modern analytics platforms and AI-assisted development tools where appropriate.
• Produce recurring and ad-hoc reports for Operations leadership and site management.
• Perform root-cause analysis on service failures, productivity gaps, capacity issues, and cost overruns.
• Translate analytical findings into clear, prioritized recommendations and measurable corrective actions.
• Establish and maintain consistent reporting definitions, data sources, and performance measurements to support a reliable single source of truth.
• Monitor trends and identify opportunities or risks before they significantly impact operational performance.

• Develop forecasting models that translate projected delivery volume into driver, team, route, and equipment requirements by location and operating day.
• Build and improve staffing and capacity models across multiple delivery and equipment types, including appliance/box-truck and van-style operations.
• Help locations maximize productive capacity and route utilization while minimizing unnecessary staffing or capacity additions.
• Support weekly, seasonal, peak, and long-range operational planning.
• Compare forecasted requirements against actual operating results and continuously improve model accuracy.
• Partner with Operations leadership to validate assumptions and adjust forecasting methodologies as business conditions change.
• Develop tools that allow operations teams to quickly understand anticipated volume, available capacity, capacity gaps, and recommended resource requirements.

• Evaluate existing operational processes and identify opportunities to improve productivity, efficiency, quality, and cost.
• Conduct work measurement, time studies, workflow analysis, capacity studies, and process observations.
• Identify bottlenecks, unnecessary steps, process variation, and other sources of operational waste.
• Develop recommendations that simplify workflows and improve consistency across locations.
• Partner with Operations management to create, improve, and streamline Standard Operating Procedures (SOPs).
• Document standard work, performance expectations, and process changes.
• Support implementation and adoption of process improvements across multiple locations.
• Measure results following implementation to ensure improvements deliver the expected operational and financial impact.

• Analyze operational cost drivers and identify opportunities to improve efficiency while maintaining service expectations.
• Evaluate driver/team compensation structures and their impact on operating cost and productivity.
• Develop financial and operational models to support driver-pay decisions and alternative compensation structures.
• Support pricing and bid analysis by evaluating anticipated volume, staffing/capacity requirements, productivity assumptions, driver pay, and other operating costs.
• Identify opportunities to improve bid profitability and protect operating margins.
• Build data-driven business cases for staffing changes, process improvements, capital/resource decisions, and commercial opportunities.
• Partner with Operations and leadership to understand the financial impact of operational decisions.

• Serve as a key Industrial Engineering and analytics partner to division Operations leadership.
• Work directly with site leaders to understand operational challenges and develop practical solutions.
• Translate complex data and analysis into recommendations that can be clearly understood and executed by operational teams.
• Present findings, trends, risks, and recommendations to Operations and executive leadership.
• Partner across Operations, Finance, Planning, People Services, and other functions as needed to support business initiatives.
• Build alignment around forecasting assumptions, capacity requirements, performance measurements, and continuous-improvement priorities.
• Travel to operating locations as needed to conduct observations, validate processes, support implementations, and work directly with site leadership.

Key Areas of Focus

• Operational dashboards and performance reporting
• Root-cause and performance-gap analysis
• Volume forecasting and capacity planning
• Driver/team requirement modeling
• Route and equipment utilization
• Work measurement and time studies
• Process improvement and SOP development
• Operating cost analysis
• Driver-pay modeling
• Bid and account profitability
• Data integrity and standardized reporting
• AI-assisted analytics, dashboard, and application development

Qualifications

• Bachelor's degree in Industrial Engineering, Systems Engineering, Operations Research, Supply Chain, Business Analytics, or a related quantitative field preferred.
• Experience in Industrial Engineering, operations analytics, supply chain, logistics, transportation, fulfillment, manufacturing, or a similar operational environment preferred.
• Experience developing dashboards, operational reporting, forecasting models, or capacity/staffing models.
• Strong proficiency with Excel and data analysis.
• Experience with business intelligence and visualization tools such as Power BI, Tableau, or similar platforms preferred.
• Experience working with SQL, Python, automation tools, AI-assisted development platforms, or similar analytical technologies is a plus.
• Experience conducting time studies, work measurement, process mapping, or continuous-improvement projects preferred.
• Experience within last-mile delivery, transportation, 3PL, distribution, or fulfillment operations is highly desirable.
• Ability to travel to operating locations as business needs require.