Parts Planning Development Engineer

Hiab is the pioneer in smart and sustainable on road load handling solutions. We believe in more than just work - we believe in making a difference for our customers to building a better tomorrow.

Say Hi! to your next challenge - explore the opportunity and apply below!

Your mission

Do you love turning unpredictable demand into high-precision inventory models? Are you ready to leverage AI, machine learning, and MEO to automate supply chain planning? Would you like your data models to directly prevent equipment downtime?

If so, we have an exciting opportunity for you as our next Parts Planning Development Engineer.

As Parts Planning Development Engineer you would be responsible for developing and improving the spare parts planning model - focusing on forecasting accuracy, inventory optimisation settings, and planning parameter configuration across the Spare Parts Supply Chain. The role works closely with the End-to-End Planning Manager and planning system Solution Owner to translate planning strategy into model improvements, and with End-to-End planners to ensure developments are practical and deliver measurable results.

This position is open to candidates based in either Gdańsk, Poland, Helsinki, Finland or Malmö, Sweden.

Key responsibilities

• Apply AI- and statistics-based forecasting models to improve accuracy across complex demand profiles, especially intermittent and slow-moving spare parts
• Configure, calibrate, and test Multi-Echelon Optimization (MEO) parameters across the distribution network to balance high parts availability with optimized inventory investment
• Analyze planning model underperformance and supply chain bottlenecks to shorten repair-part lead times and proactively prevent recurring machine downtime Vehicle Off Road (VOR) incidents
• Model and evaluate the business impact of proposed adjustments to service-level targets, network configurations, and demand assumptions for scheduled model release cycles
• Partner closely with End-to-End Planners to investigate manual intervention patterns and exception volumes, turning front-line operational feedback into automated model enhancements
• Support the deployment of planning models to new inventory locations, maintain core planning process documentation, and act as the operational backup to the Servigistics Solution Owner.

What we are looking for

• Master’s degree in Supply Chain Management, Logistics, Industrial Engineering, Applied Statistics, or a related quantitative field
• Solid background in demand and inventory planning, ideally dealing with high-variety, intermittent, or slow-moving spare parts demand patterns
• Strong foundation in statistics and supply chain theory, with the ability to translate complex mathematical models into practical planning rules
• Proficiency in analytical tools, including advanced Excel, SQL, and modern BI platforms (Power BI, Tableau, or QlikView)
• Familiarity with machine learning & AI, with a strong interest or hands-on experience in applying predictive algorithms to forecasting and inventory optimization
• Continuous improvement mindset, with exposure to Lean, Six Sigma, or structured root-cause analysis considered a strong plus.

What we offer

As a part of our Employees First culture, we offer opportunities to grow within a dynamic environment that values flexibility and your well-being. We strive to make things easier, empower you to succeed, and strive for excellence in a positive and inclusive environment.

Ready to apply?

Click on the apply button below to send in your application in English. Applications will be reviewed on a rolling basis.

We Are Hiab

Hiab (Nasdaq Helsinki: HIAB) is a leading provider of smart and sustainable on road load-handling solutions, committed to delivering the best customer experience every day with the most engaged people and partners. As the industry pioneer, Hiab continues to make on road load-handling smarter, safer and more sustainable to build a better tomorrow.

www.hiabgroup.com