Data Scientist (Large Language Model Officer) - SeRP

Swansea University
Swansea
3 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist - Renewable Energy

Job Number SU01256 Contract Type Fixed Term Salary £34,132 to £38,249 per annum Working Pattern Full Time Faculty/Directorate Faculty of Medicine, Health and Life Science Location Singleton Campus, Swansea Closing Date 11 Dec 2025 Interview Date 12 Jan 2026 Informal Enquiries

  • Emma Squires
  • Lewis Hotchkiss

Swansea University is a research-led university that has been making a difference since 1920. The University community thrives on exploration and discovery and offers the right balance of excellent teaching and research, matched by an enviable quality of life.

Our stunning waterfront campuses and multicultural community make us a desirable workplace for colleagues from around the world. Our reward and benefits, and ways of working enable those who join us to have enriching careers, matched by an excellent work-life balance.

About The Role

This is a Fixed Term role until December 2026 working full-time.

The purpose of the role is to support Swansea University’s role within the Dementias Platform UK (DPUK) collaboration, a £53 million pound public-private Medical Research Council funded endeavour to create a wide reaching and innovative dementias research facility, incorporating different research disciplines from stem-cell research to data analysis. DPUK is a world leading resource for person focussed dementias research designed to fast-track scientific knowledge, treatments and the prevention of the disease. Dementias Platform UK enables researchers to access data via a virtual desktop environment. The post offers a unique opportunity to work on a project utilising the latest AI techniques and large language models (LLMs) for developing data discovery and feasibility tools as well as personal identifiable information (PII) detection.

As a data scientist you will:

  • Work within research projects within the DPUK data portal team, including:
  • Partaking in team planning and management
  • Data preparation
  • Statistical analysis
  • Writing results for publication
  • Contribute to DPUK support activities, including provisioning data to projects, reviewing project outputs, handling researcher queries about DPUK, and helping researchers develop project ideas.
  • Work with the DPUK team to develop and test various LLM methods utilising data and metadata within the data portal and compare methods and explore opportunities/challenges in different approaches.
  • Support with the development of a user interface for users to query across DPUK data/metadata and work on PII detection projects.

Equality, Diversity & Inclusion

The University is committed to supporting and promoting equality and diversity in all its practices and activities. We aim to establish an inclusive environment and welcome diverse applications from the following protected characteristics: age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (including colour, nationality, ethnic and national origin), religion or belief, sex, sexual orientation.

As an inclusive and welcoming workplace, we value people for their skills regardless of their background. Applications are welcome in Welsh and will not be treated less favourably than those submitted in English.

Welsh Language Skills

The Welsh language level required for this role is Level 1 - A little. The role holder will be able to pronounce Welsh words, answer the phone in Welsh (good morning/afternoon) and use very basic everyday words and phrases (thank you, please etc.). Level 1 can be reached by completing a 1 hour course.

The University is a proud bilingual institution, our Welsh Language Strategy outlines our aspiration to promote the language and enable our staff to engage with the language as an additional workplace skill and as a gateway to new cultural and social opportunities. Applications are welcome in Welsh and will not be treated less favourably than those submitted in English. Welsh speakers have the right to an interview in Welsh. Applicants for a role where Welsh skills are essential are expected to present their application in Welsh and will be interviewed in Welsh, if shortlisted.

Additional Information

Applications for this role will take the format of a CV submission and cover letter.


#J-18808-Ljbffr

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 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.

Jobs

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.

Education

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.

🍪 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.