Senior Data Scientist

Swansea University
Swansea
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist/ Senior Risk Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

About The University

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 position until March 2026 working full-time.

We are seeking ambitious senior researchers to join our dynamic Population, Psychiatry, Suicide and Informatics (PPSI) team portfolio. This exciting opportunity is focused on developing innovative risk prediction tools for early-onset depression.

The team is led by Prof. Ann John, co-director of DATAMIND, principal investigator of the National Center for Mental Health, and lead of the Data Science theme in the Wolfson Centre for Young People’s Mental Health. Working within this multidisciplinary environment, you will utilize large-scale routine healthcare data to develop and validate risk-stratification models, with a particular focus on identifying young people at ultra-high risk of developing early-onset depression.

The ideal candidate will have a PhD in a relevant discipline (Epidemiology, Statistics, Data Science, Public Health, or a related field), strong programming skills (SQL, R, Python), and experience with healthcare data analysis.

If you are passionate about mental health, we invite you to apply for this position.

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 individuals with 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, and 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

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.