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Demand Planner (f/m/x)

HelloFresh · London, England, United Kingdom, København, Capital RegionDenmark, Denmark, Paris · по договорённости

Компания
HelloFresh
Город
London, England, United Kingdom, København, Capital RegionDenmark, Denmark, Paris
Зарплата
по договорённости
Уровень
middle
Формат
full_time
Иностранная компания
нанимает русскоязычных

The role: What's in the Box

We're looking for a Demand Planner who is comfortable working with data and is eager to develop their forecasting skills in a fast-paced supply chain environment. This is a hands-on analytical role: you'll spend your time writing SQL, building reports, validating forecasts, and learning how demand planning drives operational decisions.

You'll support the demand signal that drives every operational decision at HelloFresh, from how much food we order to how many staff we schedule and how many trucks we book. Your work directly contributes to reducing food waste, improving product availability, managing labour costs, and protecting customer experience for millions of meals across Europe.

Our Demand Planning team is transitioning from a legacy operating model to a unified, automated, data-driven global function. You will contribute to that transformation, supporting the build of next-generation forecasting capabilities while helping keep daily supply chain execution accurate.

What you’ll do: The Recipe

Own the day-to-day data validation and QA process across demand data pipelines. You are the first line of defence for forecast reliability, identifying anomalies, flagging data breaks, and ensuring inputs are clean before they reach the plan.

Build and maintain automated alerting for data quality issues, missing feeds, and forecast anomalies so problems are caught early, not after Operations has already acted.

Investigate discrepancies between forecast and actuals, documenting root causes and maintaining a log of known data issues to prevent recurrence.

Write and maintain SQL queries to extract, validate, and transform demand data across cloud data platforms (e.g., Databricks, Snowflake).

Support the development and refinement of forecasting models, applying statistical techniques under guidance from senior analysts, learning to work with trend, seasonality, and promotional adjustments.

Build and maintain dashboards and automated reporting using visualisation tools (e.g., Tableau) that give stakeholders access to demand insights, including key operational KPIs such as forecast accuracy, bias, waste risk, and availability.

Work alongside forecast engineers and senior analysts to support scalable pipelines, helping ensure local market nuances are handled within the unified codebase.

Use AI tools (e.g., Gemini, Claude) to speed up everyday tasks like writing SQL, debugging queries, and summarising data, we encourage experimentation with AI as part of how the team works smarter.

Support the generation and validation of daily and weekly demand plans for European markets. You'll help ensure the Decision-Time forecast is accurate at the exact moment Procurement and Production need to act.

Monitor trends, seasonality, and promotional impacts. Flag when the plan may need adjusting and escalate where appropriate.

Track forecast performance against operational KPIs, accuracy MAPE, bias, and their downstream impact on waste, availability, and fulfilment, and surface insights that help the team improve.

Participate in the weekly S&OP planning cycle, preparing materials and analysis for meetings with Market Leadership, Logistics, Production, and Procurement.

Help ensure growth campaigns and promotions from Marketing are reflected in the demand view before they hit the supply chain.

When deviations occur, support root-cause analysis: pull the data, quantify impact on waste and service levels, and help senior analysts deliver actionable insights.

What you’ll bring: The Ingredients

2–3 years in Demand Planning, Supply Planning, Supply Chain Analytics, or a related analytical role. Exposure to e-commerce, food retail, or FMCG is a plus, perishable or short shelf-life experience is a bonus.

Strong technical skills in SQL, Excel, PowerBI (or Tableau). Python is a plus.

Familiarity with forecasting concepts: you understand what bias and accuracy metrics (e.g., MAPE, WAPE) mean, why

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