Manager Group Inventory Analytics; m​/f​/d

• Full-time
• Job Function:
  Supply Chain:
  Planning, Logistics, Customer Service
• Entry Level: Professionals

Are you interested in high-quality, natural, and tasty nutrition?

We are! It’s our ambition to shape the future of nutrition.

Döhler is a leading global producer of natural ingredients and solutions for the food, beverage, lifestyle and nutrition industries. We use innovative technology to process plant-based raw materials and enrich products such as lifestyle drinks, cereals, dairy, and confectionery goods for almost every well-known brand. Close to 10.000 dedicated employees in more than 70 countries share one common goal - to ensure that millions of people around the world enjoy the products created by us.

We strive to inspire and empower our employees in everything we do, and we invite you to join our team – together WE BRING IDEAS TO LIFE.

To strengthen our Group Supply Chain Planning organization in Darmstadt, we are looking for a Manager Group Inventory Analytics (m/f/d). In this role, you will provide advanced analytics to optimize inventory across Döhler’s global end-to-end supply chain. You will develop inventory models, simulations and decision-support tools that make the trade-offs between customer service, working capital, cost, quality, supply risk, capacity and resilience transparent.

As the analytical partner to Group Inventory Management, you will evaluate replenishment strategies and provide robust recommendations for planning parameters. The position has no disciplinary responsibility and reports directly to the Manager Group Inventory Management.

• Develop and improve analytical methods for recommending safety stocks, reorder points, target stock levels, service-level settings, replenishment frequencies and related planning parameters.
• Select and apply appropriate inventory models based on demand, supply, lead-time, product and operational characteristics.
• Model demand and lead-time uncertainty, making the impact on service levels, stockout risks and inventory transparent.
• Evaluate forecast-driven, reorder-point-driven and other replenishment policies, considering review cycles, order constraints and operational realities.
• Account for relevant factors such as demand variability, seasonality, intermittent demand, supplier reliability, minimum order quantities, batch sizes, shelf life and product lifecycle effects.
• Design and conduct simulations, including Monte Carlo simulations where appropriate, to assess inventory policies, service targets, scenarios and operational constraints.
• Validate recommendations through back-testing, sensitivity analysis and scenario analysis, while documenting assumptions, logic and limitations.
• Develop and maintain scalable, reproducible analytical tools and automated workflows using Python and suitable data-processing, statistical and visualization technologies.
• Assess the quality and availability of demand, inventory, supply, lead-time, master-data and service data, and work with data owners to address limitations.
• Translate complex analyses into clear visualizations, decision materials and practical recommendations for Group Inventory Management and relevant stakeholders.
• Conduct ad hoc analyses on inventory deviations, supply and service risks, inventory build-ups, excess and obsolete inventory, and other business questions.
• Contribute to the continuous development of inventory analytics methods, tools, standards and capabilities across the global Supply Chain organization.

• University degree in Data Science, Statistics, Mathematics, Operations Research, Industrial Engineering, Supply Chain Management, Computer Science or a comparable quantitative discipline.
• 2–5 years of professional experience in inventory analytics, supply chain analytics, operations research, data science, planning analytics or a related field.
• Strong practical knowledge of inventory theory, including safety stocks, service levels, stockout risks, reorder points, target-stock logic and replenishment uncertainty.
• Experience applying statistical models, simulations, scenario analysis, sensitivity analysis or optimization methods to inventory, supply chain or operational decisions.
• Strong programming skills in Python; knowledge of SQL and relevant data-processing, statistical-analysis, visualization and simulation libraries is required.
• Experience with ERP, planning, inventory-management, APS, optimization or dashboarding tools is an advantage.
• Sound…