Inventory Management Data Analyst

Christchurch
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst (Engineering)

Data Analyst – Demand Planning & Supply Chain

Data Analyst – Demand Planning & Supply Chain

Data Analyst

Data Analyst

Data Analyst

Job Title: Inventory Management Data Analyst

Location: Christchurch, Dorset

On site / Full-time / Permanent

Salary: DOE

Job Summary:

We're looking for a detail-oriented Inventory Management Data Analyst to optimise stock levels, forecast demand, and enhance our global supply chain. You'll analyse sales trends, minimise stockouts, and collaborate with Operations and Logistics teams to drive efficiency. If you have strong analytical skills, experience in inventory management, and a proactive mindset, this role offers the chance to make a real impact in a fast-growing, dynamic environment.

Key Responsibilities:

Forecasting: Use historical data, market trends, and sales patterns to predict future product demand across different regions and channels.
Inventory Management: Monitor stock levels to ensure a balance between supply and demand, working to minimise stockouts and excess inventory.
Data Analysis: Analyse sales data and inventory performance to generate actionable insights, adjusting forecasts based on actual performance.
Collaboration: Work closely with the Operations and Marketing team members to ensure forecasts align with production and shipping schedules.
Reporting: Regularly update key stakeholders with reports on stock performance, forecast accuracy, and areas for improvement.
Process Improvement: Proactively identify inefficiencies in current stock control systems and suggest enhancements to optimise our operations.
Market Insights: Stay informed on market trends, seasonal changes, and customer demands to ensure our forecasts align with external factors.What we're looking for:

Experience: Minimum of 2-3 years of experience and a Degree in Business, Mathematics, Statistics, Data Science or other quantitative discipline.
Analytical Skills: Ability to analyse complex data, identify patterns, and make data-driven decisions - preferably in fields related to inventory management within a global, e-commerce-driven business.
Attention to Detail: Ability to spot potential stock issues before they arise and take corrective action.
Communication: Strong communication skills to interact with cross-functional teams and stakeholders at all levels.
Tech-Savvy: Familiarity with inventory management systems and forecasting software; strong experience with Excel is a must, proficiency with SQL, dbt, Python or R is a strong plus.
Proactive & Problem-Solving Mindset: You'll need to be proactive in identifying issues and finding solutions to streamline our operations and support our rapid growth.
Global Perspective: Experience in working with international markets is a plus, and understanding how to manage stock in a global supply chain is a key advantage.Why this role is exciting:

This role offers the chance to shape a fast-growing global supply chain, ensuring products reach customers seamlessly. You'll work with cutting-edge data, influence decision-making, and collaborate across teams to optimise inventory strategies. With opportunities to drive process improvements, expand into new markets, and make a tangible impact on efficiency, this is an exciting opportunity for an analytical thinker eager to solve challenges in a dynamic, high-growth environment.

Benefits:

Exciting travel opportunities and 'money can't buy' experiences.
An opportunity to be part of a passionate, innovative, and fast-growing company.
Work with a diverse team of experts in sports science, nutrition, and tech.
The chance to contribute to the development of a company making a real impact in the world of sports.INDCP

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.