VIE - Planning (m/f/d) - Germany/Austria, Frankfurt am Mai / Munich / Vienne

Danone

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Company

Danone

Place(s)

Frankfurt am Main, München, Vienna
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VIE - Planning (m/f/d) - Germany/Austria, Frankfurt am Mai / Munich / Vienne

Voluntary
Food
Logistics
Offer archived at 24/07/2026
 

Danone

Danone is a global leader in the food industry, operating in three fast-growing categories: dairy and plant-based products, water, and specialised nutrition. True to our mission of bringing health through food to as many people as possible, our ambition is to inspire healthier and more sustainable eating and consumption habits. We are committed to making a positive and measurable impact on nutrition, society and the environment.

Mission

  • Accountable for the creation of precise short- and mid‑term demand forecasts for key customers, working closely with cross-functional stakeholders
  • Analyze market trends, historical data, and key business drivers to improve forecast accuracy
  • Monitor forecast performance and identify root causes of deviations
  • Ensuring consistency of forecast from period to period, tracking and explaining changes
  • Understand business and demand levers to manage ad-hoc requests and drive operational actions
  • Close relationship with Sales, Marketing and lively exchange within the supply chain cluster
  • Support on our roadmap to enhance our forecasting by AI

Profile

  • Currently pursuing a degree in Business Administration or a related field, ideally with a focus on Supply Chain Management (SCM) or Logistics.
  • Some practical experience in planning processes is desirable.
  • Basic knowledge of Excel; experience with SAP / IBP is a plus.
  • Analytical mindset with the ability to maintain attention to detail while keeping an eye on the big picture, and the confidence to challenge assumptions when needed.
  • Good communication skills and the ability to easily connect with others.
  • Proactive attitude and willingness to take initiative.
  • Fluency in English is required to ensure effective collaboration with international stakeholders.
  • Eager to develop and implement statistical and machine learning forecasting methods to drive continuous improvement in forecasting performance.

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Offer archived at 24/07/2026

 
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