Clinical Logistics Specialist

IQVIA
Reading
1 year ago
Applications closed

Related Jobs

View all jobs

Clinical Data Scientist – CODU, Manchester

Senior Clinical Data Scientist, CDM Europe (Hybrid)

Principal Clinical Data Science Lead for Trials & CRO

Sr Clinical Data Scientist CDM (Hybrid - Europe)

Data Engineer - Build Scalable Data Pipelines and Analytics

Technical Program Manager - Machine Learning - New York

IQVIA is looking for a Clinical equipment delivery specialist with exceptional customer service skills.

You will be covering the M4 Corridor area working within the Sales/Supplier/Logistics team to support the safe delivery of surgical equipment to hospitals. You will need be comfortable with navigating your way around a hospital setting, able to identify the right people and department to ensure the smooth, on time delivery of medical equipment in line with company standards.

It will be your responsibility to orgainse the logistics, making sure the right kit is in the right place at the right time, working closely with your internal supplier management team as well as clinical staff at your client site. You will ensure the accurate completion of paperwork and inventory management systems. Exceptional customer service skill is required to provide the highest quality and timely service for each delivery.

This will ideally suit someone who is looking to have a career in medical devices sales in a clinical hospital theatre setting and could be a steppingstone into sales.

This role is a full-time position, offering a competitive salary plus bonus and a small company van. Mandatory requirement of a full driving license with no more than 6 minor points.

Key Responsibilities:

Coordinate with Sales Team, Customer Services, Supply Chain, Warehouse, and Clinical Theatre Staff to ensure timely delivery of surgical kits. Manage urgent movement of Implants and Instruments Trays between hospitals. Record and reconcile borrowed implants to ensure replenishment and accurate invoicing. Resolve DNA issues and ensure complete loan kits for collection. Assist with kit preparation, sterilization, and packing processes. Support regional SLOB initiatives and assist with Out of Date implant management. Collaborate with S&OP team for Inventory Audit reconciliations. Aid new business wins by deploying account consigned inventory. Occasionally provide weekend logistics support.

Required skills and experience:

Exceptional communication skills and ability to build strong relationships. Highly organised with excellent task prioritisation abilities. Thrives under pressure and demonstrates initiative in problem-solving. Familiarity with inventory and supply chain processes. Insight into the medical technology industry and orthopaedic market. Confident driver.

If you are seeking a challenging and rewarding role that allows you to contribute to the success of a leading Med Tech organisation while working with cutting-edge orthopaedic products, APPLY TODAY.

Please note: Sponsorship is not available for this opportunity

#LI-DNI

#LI-LJ1

IQVIA is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry. We believe in pushing the boundaries of human science and data science to make the biggest impact possible – to help our customers create a healthier world. Learn more at

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.