Demand Planner

Leeds ICD
1 week ago
Create job alert

Demand Forecasting Specialist

Arla Head Office, Leeds, LS10 1AB

Permanent, days-based role (Monday-Friday, 37.5 hours per week)

We are currently seeking a Demand Forecasting Specialist to join our team. This role will provide essential support to our Finnish market and colleagues, whilst working alongside our UK Demand Planning team.

What do we offer?

  • Competitive salary (salary discussed at application stage)

  • 26 days holiday & Bank Holidays

  • Hybrid & flexible working

  • Pension contribution matched up to 6%

  • 4 x annual salary life assurance

  • Free to use onsite Gym

  • Access to discounted products in our Staff Shop

  • People agenda commitment to training and development

  • Flexible Benefits- buy up to 5 days additional annual leave, reward gateway scheme- discounts with various retailers via my benefit platform.

  • Most importantly - Cheese hamper at Christmas!

    How will you make an impact?

    Reporting into the Demand Planning Manager in Finland, this role will play a pivotal part in improving planning efficiency through data analytics and advanced forecasting. Key responsibilities include data assessment, maintaining baseline forecasts, and applying machine learning for accurate forecasting. A deep understanding of demand patterns, product lifecycles, and market trends is essential.

    Further responsibilities include;

  • Maintain master data and planning parameters for demand planning, and ensure data completeness and quality.

  • Review automatic cleansing processes and ensure the final output (cleansed data) is completed in the system.

  • Generate and analyse historical demand performance reports, incorporating relevant actions into future forecasting. Provide initial baseline forecasts for phase-in/phase-out products.

  • Select and manage appropriate statistical models for demand segmentation, and run and adjust statistical baseline forecasts and advanced modelling.

  • Monitor and report on forecasting KPIs, and provide descriptive and diagnostic insights about previous cycle’s forecast performance.

    What will make you successful

    The ideal candidate will have;

  • Strong experience within demand planning and demand planning systems (Experience with SAP IBP is a strong advantage)

  • Excellent data and analytical skills

  • Experience within a fast-paced FMCG environment is preferrable.

  • Technical proficiency

  • Possesses strong collaboration, organisation and teamwork skills

    Would you like to join us?

    If you are enthusiastic about joining our team and meet the qualifications listed above, we would love to hear from you. Please apply as soon as possible as we will process applications on a continuous basis and close the recruitment once the right candidate is found.

    For additional information, please contact Olivia Pine, Talent Acquisition Partner at Arla Foods. The closing date for this position is the 21st April 2025 and only CV’s sent directly via the link will be considered

Related Jobs

View all jobs

Demand Planner

Customer Service & Sales Support Associa

Customer Service & Sales Support Associate

Mechanical Inspector

Data Quality Analyst

VP, Strategy Analytics (Basé à London)

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.

Data Science vs. Data Mining vs. Business Intelligence Jobs: Which Path Should You Choose?

Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.