Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

QA Scientist Analyst - GSK0JP00106075

Worthing
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Director of Data Science & Insights

2026 Junior Data Scientist (Graduate) - London

2026 Junior Data Scientist - London

Senior Data Science Strategist - Featurespace

Data Quality Engineer

Senior Data Science Engineer, American Football

Job Title: QA Scientist Analyst

Job Type: 6 Month Contract

Employment Start Date: ASAP

Onsite requirement: 5 days per week on site

Industry: Pharmaceuticals

Location: Worthing, England

Salary: £15.64 per hour - PAYE

SRG are working with a global leader in the pharmaceutical industry to find a new QA Scientist Analyst for their site in Worthing.

Responsibilites:

To test routine production and stability samples supplied from the site Value Streams and meet testing lead-time targets.

Calibrate and maintain analytical equipment.

Carry out qualitative and quantitative analysis of antibiotic powders and solid dose forms using a wide range of analytical techniques (eg: HPLC, Karl Fischer, dissolutions etc).

To carry out OOS investigations and discuss the outcome with Team Leader, or relevant production Dept, QA manager or a Qualified Person, as required.

To check and verify analytical testing and data generated by other analysts

To adhere to and help maintain the highest levels of safety and GLP within the section and ensure training records are kept up to date.

Perform validation of equipment and methods as required

Daily liaison with both other analysts and team leader regarding testing and test results. May be required to take a lead role within a small team of analysts working together on a common analytical technique e.g. HPLC.

Supplying data / reports to Value Stream as requested.

May be required to communicate with the relevant Value Steam. to progress OOS investigations

Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.