Inventory Data Analyst

Agora Talent
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

ERP Lead Data Analyst

ERP Lead Data Analyst

Media Data Analyst

Collections Metadata Analyst (Library focus)

Supply Chain Analyst

Data Analyst

My client, a growing luxury accessories brand, is seeking an Inventory Data Analyst to play a key role in optimising stock management and driving operational efficiency. This is an exciting opportunity to join a fast-scaling business where your expertise in inventory control, data analysis, and stock auditing will directly contribute to its continued success.



With ambitious growth plans, this role offers room to develop and take on more responsibility, making it ideal for someone who thrives in a dynamic, high-end retail environment and wants to grow with the company.


Key Responsibilities:


Data Integrity & Reconciliation:

  • Ensure accurate inventory records through regular reconciliations and audits.
  • Investigate discrepancies and collaborate with finance, production, and retail teams to resolve stock-related issues.


Stock Audits & Reporting:

  • Lead stocktakes across various departments, using advanced Excel functions (index/match, nested IF statements, XLOOKUPs, pivot tables, and macros) to track and analyse data.
  • Prepare monthly reports on key inventory metrics, stock levels, and discrepancies, offering actionable insights to senior management.


Process Optimisation & Compliance:

  • Identify root causes of stock discrepancies and drive process improvements to minimise inventory losses.
  • Develop and maintain SOPs for inventory control, ensuring best practices across the business.
  • Train cross-functional teams on inventory processes and system usage.


Operational Support & Collaboration:

  • Work closely with finance and operations teams to manage inventory adjustments and intercompany stock transfers.


Skills & Experience Required:

  • Experience in inventory control, data analysis, and stock auditing.
  • Advanced Excel skills, with proficiency in formulas, pivot tables, and macros
  • Familiarity with ERP systems and inventory management platforms.
  • Inventory analysis experience in either fashion, accessories or luxury is desirable.
  • Strong analytical skills with the ability to interpret large datasets and present insights to senior stakeholders.
  • Detail-oriented, with the ability to manage multiple priorities in a fast-paced environment.


This is a fantastic opportunity to join a leading luxury retail brand and play a pivotal role in optimising inventory operations. If you have the expertise and passion for data-driven inventory management and a proven background in either fashion, beauty, luxury or the consumer sector, please apply now!

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.

Jobs

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Jobs

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Jobs

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

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.