Döhler, a leading global producer of natural ingredients and solutions for food, beverage and nutrition, is hiring a Manager Group Inventory Analytics (m/f/d) for its Group Supply Chain Planning team in Darmstadt. You will build inventory models, simulations and decision tools that balance service, working capital, cost, quality and risk across a global supply chain.
About Döhler
Business: Natural ingredients and solutions for food, beverage, lifestyle and nutrition
Scale: Close to 10,000 employees in more than 70 countries
Technology: Innovative processing of plant-based raw materials
Motto: WE BRING IDEAS TO LIFE
Why Join Döhler?
Ownership: Space to take initiative and share ideas
Growth: Flexible development across departments and a global team
Environment: International team with multiple cultures and languages
Reporting: Directly to the Manager Group Inventory Management
Position Overview
As Manager Group Inventory Analytics, you act as the analytical partner to Group Inventory Management. You develop methods to recommend safety stocks, reorder points, target stock levels, service levels and replenishment frequencies, and you model demand and lead-time uncertainty. You design and run simulations, including Monte Carlo, validate results through back-testing and scenario analysis, and build reproducible Python tools and automated workflows. You also turn complex analyses into clear visuals and recommendations and run ad hoc studies on excess and obsolete inventory, supply risks and service issues.
Why This Role Matters: Inventory decisions tie up working capital and decide whether customers get their products on time. This role puts advanced analytics at the centre of a global supply chain, offering a quantitative professional the chance to influence real planning parameters at a leading ingredients company.
Key Responsibilities
Inventory Models
- Develop methods for safety stocks, reorder points, target stock levels and service levels
- Select suitable inventory models for demand, supply and lead-time characteristics
- Model demand and lead-time uncertainty and show effects on service and stockouts
Simulation & Validation
- Design simulations, including Monte Carlo
- Validate recommendations through back-testing, sensitivity and scenario analysis
- Document assumptions, logic and limitations
Tools & Insights
- Build scalable, reproducible Python tools and automated workflows
- Assess data quality and work with data owners
- Present clear visuals and recommendations, and run ad hoc analyses
Qualifications & Requirements
Education & Experience
- University degree in data science, statistics, mathematics, operations research, industrial engineering, supply chain management, computer science or similar
- 2–5 years in inventory, supply chain or planning analytics, operations research or data science
Technical Skills
- Strong knowledge of inventory theory: safety stock, service levels, stockout risk, reorder points
- Experience with statistical models, simulation, scenario analysis or optimisation
- Strong Python and SQL skills; experience with ERP, APS or dashboarding tools is an advantage
Personal & Languages
- Structured problem solving and analytical rigour
- Strong communication and stakeholder management
- Business-fluent English; German is an advantage
About Döhler
Döhler is a leading global producer of natural ingredients and solutions for the food, beverage, lifestyle and nutrition industries. It processes plant-based raw materials for lifestyle drinks, cereals, dairy and confectionery for almost every well-known brand, with close to 10,000 employees in more than 70 countries.
How to Apply: Apply through the Döhler online career portal. Documents sent by post cannot be considered. You can also try the Culture Fit Challenge mentioned in the posting.
Who Should Apply?
- Supply Chain Analysts: With inventory and planning experience
- Operations Research Specialists: Who like simulation work
- Data Scientists: Looking for applied supply chain problems
- Python Analysts: With SQL and statistics skills
- FMCG and Food Industry Planners: Moving into analytics
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