Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Demand Planner

London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist - Demand Forecasting

Data Scientist - Demand Forecasting

AI Data Engineer

Demand Planning Data Analyst

Google Cloud AI/ML Data Engineer

Data Engineer - no experience necessary

Pod is thrilled to be partnering with a fast-growing startup seeking a Demand Planner to join their expanding London team! (3 days in the office).

In this newly created role, you'll be responsible for developing accurate demand forecasts, optimising inventory, analysing sales data, collaborating with key stakeholders, and driving continuous improvements in demand planning.

This is an exciting opportunity to be part of a dynamic, ambitious brand where you’ll have the freedom to shape your own growth and development.

In this role, 
you will...

Develop accurate short- and long-term demand plans using historical data, market trends, and collaboration across teams
Monitor and optimise stock levels, balancing availability with minimising excess and storage costs
Analyse demand patterns and sales performance, providing regular reports on forecast accuracy and trends
Work closely with key teams on promotions and market shifts; lead weekly demand planning meeting
Enhance forecasting accuracy, planning tools, and inventory management while maintaining data integrity in demand planning systems
About you...

Proven experience in demand planning or merchandising within an FMCG organisation
Strong numerical and Excel skills 
Build successful relationships internally and externally in order to enable seamless communication
Experience working in a fast-paced environment and desire for continuous improvement
Ability to handle complex analytical problems
If interested, please feel free to apply directly

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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 Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.