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zooplus SE

Demand Planning Manager (All Genders)

London
€36.6k – €55k/yr
Posted about 18 hours ago
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Company Description

With over 25 years’ experience, plus the same enormous passion and ambition we had on day-one, we’re trailblazers in the pet e-commerce industry. Our solutions make over 12 million customers genuinely happier – and that’s something we really care about. We work together to continually adapt; embracing change and the challenges it brings so that we can keep doing better. Join us and discover a place where your potential meets your passion for pets. That’s the power of plus.

Job Description

The duration of this role is fixed, and the contract will have a length of 12 months.

As a Demand Planner Manager – Stock Keeping Unit (Replenishment), you’ll manage and improve inventory forecasts to ensure optimal stock levels and drive efficient replenishment. You’ll own medium-term forecasting, track forecast accuracy, and work cross-functionally to support supply chain performance. The role also includes scenario planning, risk management, and contributing to S&OP meetings to address supply challenges and opportunities.

Your tasks:

  • Medium-Term Forecast Ownership
    • Track projected inventory by Country, Brand, Category
    • Own and refine our 6-month rolling forecast, using input from other forecasts, planned promotions, historical trends, and stock levels.
    • Monitor forecast accuracy and drive improvements.

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  • Replenishment Planning

    • Trigger replenishment orders based on forecast and target stock levels.
    • Define and maintain reorder points, safety stock levels, and min/max thresholds.
    • Represent demand planning in S&OP meetings, providing insights on forecast accuracy, supply constraints, and campaign feasibility.
  • Scenario Planning & Risk Management

    • Run what-if scenarios for demand surges, supply delays, or promotional changes.

Qualifications

  • 2–5 years of experience in demand planning, inventory planning, or supply chain management with e-commerce experience preferred
  • Understanding of inventory KPIs, replenishment models, etc.
  • Ability to synthesize and communicate with both commercial and operational teams.
  • Strong Excel/spreadsheet modeling with a first formal experience in SQL and Python is required.
  • Understanding of Regression techniques would be a plus.

Working language: English

Additional Information

Headquartered in Munich, with offices across Madrid, Krakow, Wroclaw, London, and Vienna, we collaborate because we genuinely love working together - so you’ll be at the heart of an incredible, multinational team. We trust each other to get the job done, which means you’ll benefit from hybrid working, spending 60% of your time in the office and 40% at home. There’s an option to work for 20 days abroad in approved countries too.

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Add to that development opportunities that help you to shape your own career path, excellent training and support, wellbeing offers, subsidized transport or bike leasing, plus 20% discount across all our products, and you’ll begin to get a sense of what sets us apart. Find out more about the specific benefits at your local office in our blog posts.

A note on compensation: We believe in being transparent about salary ranges. The range shown reflects the full scope that the role can grow into over time, depending on experience, skills, and impact. Most offers are positioned around the midpoint of the range, ensuring a fair and consistent approach across our teams.

At zooplus, we believe in equal opportunity and support everyone to fulfil their potential. We recognise the power of listening and learning from each other and embrace diversity and inclusion of all.

#LI-Hybrid

Department: Sales & Marketing

Job Level: 06

Career Stream: Individual Contributor (Expert)

Compensation: EUR 36600 - EUR 55000 - yearly

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Skills

Demand planning
Inventory planning
Supply chain management
Forecasting
Replenishment models
Inventory KPIs
Excel
Spreadsheet modeling
SQL
Python
Regression techniques
Scenario planning
Risk management
S&OP
Data analysis

Location

London, England, United Kingdom

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