Inventory Management Data Analyst

Christchurch
1 month ago
Applications closed

Related Jobs

View all jobs

Supply Chain Data Analyst

Data Analyst

Data Analyst

Business Analyst - Trading Controls

Senior Analyst

Unit Coordinator

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

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.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.