Demand Planner

Fender
East Grinstead
3 months ago
Applications closed

Related Jobs

View all jobs

Demand Planner

Lead / Senior Applied Data Scientist - Causal AI for Demand Forecasting

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM London, United Kingdom

▷ Urgent! Sr. Data Scientist / Machine Learning Engineer -GenAI & LLM

Principal Data Science Consultant - Financial Services Expertise

Principal Data Science & ML Engineering Consultant

We are searching for a Demand Planner to join our team. The Demand Planner function will include the development and upkeep of accurate short, mid, and long-term forecasts, ensuring alignment of supply with customer demand in accordance with budgeted inventory policies. This role involves independently working to build and maintain service levels within the Supply Chain, fostering relationships with partners, customers, and third-party warehouses. You will also look to lead improvement projects within the Planning and Supply Chain.Essential Functions: Play an active role in supporting the monthly SIOP process, being the back up for the Supply Chain Manager in key process meetings.Balancing demand with supply while keeping within inventory targets, using relevant demand planning tools.Working with Sales, Product Managers and Marketing to review and agree on demand forecasts, complementing system generated forecasts.Monitor trends in customer orders against forecast and identify forecast improvements.Maintain forecasts in line with inventory and business rules where relevant.Manage supply issues and develop alternative plans where delivery schedules cannot be improved.Manage New Product Introduction and End of Life processes in conjunction with Sales, Product Managers and Marketing to ensure that slow moving and excess inventory is minimised.Work closely with Sales & Product Managers to reduce Excess and Obsolete Inventory.KPI reporting and control analysis on measures such as (but not limited to) Inventory, Forecast Accuracy, Fill Rate, Slow Moving, New Product Introduction and Excess InventoryAbility to document processes, write training material for any reporting/tools created.Develop relationships with various functions to obtain data, learn business processes; be the advocate for supply chain in any additional reporting/tools needed. Essential Skills/Knowledge: Graduate calibre with proven experience of Demand Planning and/or Inventory PlanningSAP experience a plusExperience with Amazon and BTC a plusExperience with Data Science techniques such as, but not limited to, Decision Tree, Linear and Logistic Regression, Naïve Bayes, k-Means and Neural Networks a plusWorking knowledge of Logility (or similar) planning softwareStrong PC skills with experience of Microsoft packagesCommercial and financial awareness and acumenA self-starter who needs limited guidance as to what/how to analyse data. Curious with a desire to get to the root cause.Develop tools/spreadsheets/processes to aid in data analysis and to understand and optimise/improve processes; make recommendations for changes.Comfortable communicating across multiple layers in the organisation, can deliver 'bad news' and resolve differing points of view.

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.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.