Inventory Data Analyst

Manpower
Bridgwater
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst – Demand Planning & Supply Chain

Data Analyst

Data Analyst (Engineering)

Data Analyst

Role -Inventory Data Analyst

Location -Bridgwater

Pay rate -£145 per day

Hours -Full- time 37 hours per week, working Monday - Friday.

A career that will deliver change.

The Opportunity

We are seeking an experienced and competent Catalogue Inventory Analyst to join a growing asset data management team. The individual will ideally come with extensive previous cataloguing and analytical experience, data entry and validation related knowledge and skills, and rapidly grow to become a key member of a small but dedicated Enterprise Asset Management (EAM) data management team.

The Role

Accurate and timely population of the Inventory module of the Asset Suite 9 EAM Tool with requisite information relating to asset equipment and bulk materials, including unique asset identifiers and the associated set of pre-defined asset data attributes, to support their timely and accurate call off from the warehouse to HPC site. Complete the quality assurance of all Catalogued assets as a key enabler to both their fully auditable call off, installation and management of the plant's configuration reference. Maintain a predefined asset cataloguing schedule, working closely with the line manager to proactively identify and manage any data verification issues and anomalies, so maintaining responsibility for data integrity and load schedules Producing weekly cataloguing performance reports into the line manager for review, approval and upward reporting. Work independently to achieve targets but in conjunction within the existing AS9 Work Management Team(WMT) to support broader team targets and the delivery of consistent and verified data and/or documented references across a number of integrated IS platforms.

The Skills

The ideal candidate will possess proven asset cataloguing, data analysis, verification and entry skills and a capacity to logically process data (and documentation), whilst both identifying data inconsistencies and managing their resolution independently, or where required, with a senior member of the team. The successful candidate will possess specific prerequisite skills and qualifications including:

A solid track record of digital cataloguing and assured data entry, and/or using SAP and/or EDRM databases. Previous experience of working in a construction, supply chain, procurement and/or data management related industry. A proven track record of adept and precise data and documentation management skills. A proven ability to work without supervision is essential. Proficient use of Microsoft products including MS: Excel; Word,and Powerpoint. Knowledge of Asset Suite/Passport will be advantageous but is not essential.

null

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.

Careers

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.

Jobs

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.

Careers Jobs

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.

🍪 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.