Buyer

Middleton
1 year ago
Applications closed

We are primarily an Oil and Gas company, however in Manchester we mainly produce product for the industrial markets providing PC Pumps and Mixers.
As a Buyer you will utilise professional procurement practices to obtain goods and services to contribute to the delivery of our products to allow successful integration into our customers’ working plant, ensuring high quality, cost effectiveness and timely delivery of purchased items or services.
You will take ownership of projects from a Supply Chain perspective, engage and develop strong relationships with current and potential suppliers to maximise commercial advantage in line with quality programs and initiatives, you will also work with all internal contacts to ensure the customer requirements are met. You should be keen to take on fresh challenges, develop your technical and interpersonal skills as well as expand your knowledge and experience through a variety of exciting projects.
DUTIES AND RESPONSABILITIES OF A BUYER:

  • Production and Inventory Planning: Establish and maintain production, material, inventory, and purchase plans to support the master schedule.
  • Delivery and Supplier Management: Plan deliveries, manage supplier lead times, customer needs, and achieve inventory goals.
  • Order Tracking and Resolution: Track purchase order status, resolve past due orders, invoicing errors, or supply interruptions.
  • Data Integrity: Review and maintain the integrity of master data, including item master and BOMs for assigned product lines.
  • Liaison: Collaborate with commercial teams on delivery and availability issues and with inter-company teams on material planning and forecasting.
  • Competitive Sourcing: Lead competitive sourcing and purchase negotiations for low-value processes.
  • Improvement Projects: Participate in projects aimed at reducing costs, inventory, and lead times.
  • Vendor and Quality Management: Monitor service levels and the quality of products received, liaise with overseas vendors, and investigate VMI opportunities.
  • Stakeholder Collaboration: Collaborate with key stakeholders internally and externally to ensure project success.
  • Project Documentation: Ensure timely issuance of project documentation by liaising with various departments.
    SKILLS AND EXPERIENCE REQUIRED BUYER
    Essential:
  • Manufacturing discipline in Engineering or experience as a Buyer in the Manufacturing industry.
  • Previous experience and working knowledge of procurement methods, procedures, and processes.
  • Technical understanding of manufacturing, fabrication, assembly, machining, and inspection techniques.
  • Working knowledge of ERP systems (e.g., JDE).
  • Proficiency in Microsoft Office (Excel, Word, Outlook).
  • Ability to interpret engineering documents and drawings.
    Desirable:
  • APICS or MCIPS Certification.
  • Experience in a project-based environment.
  • Knowledge of Machinery, PED, and ATEX Directives.
  • Experience in industrial mixing applications.
  • Strong negotiation skills.
  • Critical path management skills.
    A flexible benefits program for you and your family through salary sacrifice:
  • Dental Insurance
  • Healthcare Cash Plan
  • Partner Life Assurance
  • Critical Illness
  • Retail vouchers
  • Gym membership
  • Cycle to work
  • Travel insurance
    Why Join Us?
    At NOV, you will have the opportunity to work in an international environment with interesting and challenging assignments. We offer excellent opportunities for professional development, attractive compensation, and stable employment conditions. You will be part of an informal working atmosphere, characterized by openness and personal responsibility, working alongside skilled professionals on diverse and impactful projects.
    About Us
    Every day, the oil and gas industry’s best minds put more than 150 years of experience to work to help our customers achieve lasting success.
    We Power the Industry that Powers the World
    Throughout every region in the world and across every area of drilling and production, our family of companies has provided the technical expertise, advanced equipment, and operational support necessary for success—now and in the future.
    Global Family
    We are a global family of thousands of individuals, working as one team to create a lasting impact for ourselves, our customers, and the communities where we live and work.
    Purposeful Innovation
    Through purposeful business innovation, product creation, and service delivery, we are driven to power the industry that powers the world better.
    Service Above All
    This drives us to anticipate our customers’ needs and work with them to deliver the finest products and services on time and on budget

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 Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.