Specialist, Logistics Optimization

Domtar is a leading producer of pulp, paper, packaging, tissue and wood products. Through our focus on safety and sustainability, as well as our commitment to operational excellence and our network of facilities across Canada and the United States, Domtar delivers high-quality and cost-effective products to customers around the world.

Our workforce is comprised of 14,000 talented and hardworking individuals. We are proud to offer competitive compensation, a supportive working environment, rewarding career paths and plenty of opportunities for learning and growth.

The location in Montreal, Quebec, Canada, is seeking talent to fill the position of Specialist, Logistics Optimization. This job is full-time permanent.

Would you like to play a key role at the intersection of data, advanced analytics, optimization, and commercial logistics?

This position offers the opportunity to directly contribute to the financial and operational performance of the Wood Products business by developing analytical tools, decision-support models, and automation solutions that support the organization’s logistics strategies. You will be a central contributor in identifying cost optimization opportunities, improving transportation network performance, and transforming analytical practices.

Your analyses and recommendations will directly influence decisions related to transportation costs, routing strategies, commercial negotiations, and supply chain efficiency.

Your challenges

You will serve as the subject matter expert for data, analytics, optimization, and automation within the Commercial Logistics team. In this role, you will:

Actively participate in the identification, evaluation, and implementation of supply chain optimization initiatives that generate measurable financial gains;

Develop analytical models to optimize transportation costs, routing strategies, and overall logistics network performance;

Ensure the availability, reliability, and integrity of data used in commercial and operational decision-making;

Support logistics specialists and the logistics manager in conducting quantitative and financial analyses aimed at maximizing profitability;

Play a key role in digital transformation, automation, and analytical systems improvement projects.

More specifically, you will focus on the following areas

Identify and recommend logistics network optimization initiatives (cost, capacity, service, lead times, and routing);

Conduct advanced cost, profitability, and business scenario analyses to support decision-making;

Produce and automate cost-benefit analyses that support commercial and strategic decisions;

Support logistics specialists during supplier negotiations by providing quantitative analyses and comparative scenarios;

Structure and model data to improve the speed, quality, and accuracy of business decisions;

Ensure the integrity, consistency, and availability of data within the ERP system and analytical tools;

Establish and maintain data governance and data quality control processes;

Develop, optimize, and standardize the analytical tools used by the team (advanced Excel, Power BI, Power Automate, Power Apps, databases);

Design and maintain dashboards and performance indicators used to monitor costs, realized savings, and logistics performance;

Automate manual processes to increase operational efficiency and reduce low-value-added activities;

Act as a liaison between business teams, IT teams, and external partners to develop value-creating solutions.

Your team

Reporting to the Commercial Logistics Manager, you will join a results-oriented team where data, innovation, cost optimization, and continuous improvement are at the heart of decision-making.

You will have the opportunity to directly influence the organization’s logistics and financial performance by developing high-impact analytical solutions.

Your profile

University degree in Operations Research, Industrial Engineering, Business Analytics, Supply Chain Management, Information Systems, or a related field;

2 to 5 years of experience in data analysis, optimization, process improvement, or decision-support tool development;

Demonstrated experience identifying and implementing optimization or cost-reduction initiatives;

Strong understanding of logistics and supply chain operations (truck, rail, marine, or intermodal transportation is a significant asset);

Experience with ERP systems and advanced analytical tools;

Advanced proficiency in Excel (Power Query, Power Pivot, or equivalent);

Advanced proficiency in Power BI;

Experience with Power Automate, Power Apps, and digital transformation platforms;

Knowledge of SQL, Python, or other quantitative analysis tools is considered a significant asset;

Strong interest in process optimization, automation, and continuous improvement.

Your skills

Excellent analytical skills and ability to solve complex problems;

Strong results-oriented mindset and focus on value creation;

Ability to transform data into actionable business recommendations;

Ability to translate business needs into analytical and technology solutions;

High level of rigor in data management, validation, and interpretation;

Ability to manage multiple priorities in a fast-paced environment;

Ability to influence decisions through fact-based and structured analyses;

Leadership in transformation and continuous improvement initiatives;

Excellent collaboration skills with multidisciplinary teams;

Strong communication skills in both French and English;

Initiative, intellectual curiosity, and a passion for optimization.

Domtar is firmly committed to placing greater emphasis on the principles of equity, diversity and inclusion to empower all employees to reach their full potential. We form a dynamic team whose diverse backgrounds and wealth of perspectives are one of the keys to our success. We offer an inclusive, rewarding and safe work environment with opportunities that will help grow your skills.

To learn more about our company, consult the Domtar Company Web Site and follow us on LinkedIn, Instagram and Twitter.