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Inventory Optimization Analyst

@ Parts for Trucks, Inc.

Dartmouth, Nova Scotia

Full-time
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SIGNALS

Requirements summary:

  • Degree in Supply Chain, Industrial Engineering, Operations Research, Business Analytics, Data Science, Statistics, Computer Science, or a related field.
  • 3+ years of experience in inventory analytics, demand planning, supply chain analytics, data science, or operations research.
  • Strong experience building software models to analyze, forecast, and optimize operational data.
  • Experience with forecasting, replenishment, inventory optimization, and data visualization.
  • Ability to communicate complex analysis to non-technical stakeholders and influence business decisions.
  • Experience in wholesale distribution, aftermarket parts, industrial distribution, transportation, or supply chain planning.
Source and dates

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Employer posting date
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First seen by our source
2026-11-14
Source record updated
2026-11-14

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Parts for Trucks, Inc.

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Job description

Parts for Trucks has been an industry leader providing parts and service to the heavy-duty trucking industry for over 100 years. Operating coast to coast, Parts for Trucks offers a complete range of products and services for all makes of trucks and trailers. We take pride in our commitment to quality, customer satisfaction, and reliability.

Turn data into smarter inventory decisions.

Parts for Trucks is seeking an experienced data scientist in inventory analytics to help optimize inventory across our national branch and distribution network. This is a high-impact role focused on inventory analytics, forecasting, replenishment, and data driven decision-making using SQL, Python, Power BI and other modern analytical tools.

What you'll do:

  • Analyze inventory, sales, purchasing, and replenishment data.
  • Develop recommendations for inventory levels, safety stock, reorder points, and inventory positioning.
  • Build forecasting and optimization models using Python or other coding languages.
  • Create dashboards and decision-support tools using SQL and Power BI.
  • Partner with Inventory Management, Purchasing, Operations, and IT to improve product availability, inventory turns, and working capital position.

What you'll bring:

  • Degree in Supply Chain, Industrial Engineering, Operations Research, Business Analytics, Data Science, Statistics, Computer Science, or a related field.
  • 3+ years of experience in inventory analytics, demand planning, supply chain analytics, data science, or operations research.
  • Strong experience building software models to analyze, forecast, and optimize operational data.
  • Advanced SQL skills for data extraction, validation, and analysis.
  • Experience with forecasting, replenishment, inventory optimization, and data visualization.
  • Ability to communicate complex analysis to non-technical stakeholders and influence business decisions.

Preferred

  • Experience in wholesale distribution, aftermarket parts, industrial distribution, transportation, or supply chain planning.
  • Experience with inventory optimization, demand forecasting, machine learning, or operations research.
  • Experience with Microsoft Power Suite (BI, Apps, Copilot), ERP systems, and cloud analytics platforms.
  • Experience implementing recommendations and measuring business outcomes.

Why join Parts for Trucks?

  • Build a new inventory analytics capability from the ground up.
  • Work directly with business leaders and operational teams.
  • See your recommendations implemented and measured.
  • Competitive compensation, benefits, and flexible hybrid work options.

If you enjoy solving complex supply chain problems and turning data into business results, we'd love to hear from you.

Parts for Trucks is an equal opportunity employer. We value a diverse and inclusive workplace and are committed to equitable hiring practices. We thank all applicants for their interest. Only those selected for an interview will be contacted.

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