Data Scientist

King's College Hospital NHS Foundation Trust
London
4 months ago
Create job alert

Job overview

Neuropsychology services generate a wealth of psychometric assessment data, which is critical for understanding patient profiles, informing clinical decisions, and supporting service development. However, much of this data remains siloed in local records, limiting its potential for broader analysis and quality improvement.


The proposal is to digitise local neuropsychology assessment data for use in downstream analysis. This will involve engaging with the internal data science team and developing tools to interrogate both locally and cloud-stored information. The resulting infrastructure will support internal audits, facilitate service performance reviews, and empower locally inspired research projects.


A key component of this initiative is the creation of a registry designed specifically for neuropsychology assessment data; to enable systematic evaluation of patient outcomes and service delivery, providing a valuable resource for audit, service evaluation, and research. It will also help identify trends and inform future clinical practice.


The post-holder will play a central role in this work, collaborating with the data science team to develop and maintain the necessary analytics platforms and data infrastructure. Responsibilities will include contributing to quality management, ensuring compliance with national standards and regulations, and helping to shape data governance processes for the use of digitised assessment data in both clinical and research contexts.

Main duties of the job

Developing machine learning models to enhance efficiency in the neuropsychology department by optimizing diagnositic patient assessment


Develop code to streamline data collation, identify the most specific and sensitive diagnostic tests, and eliminate redundancy.
Benchmarking and fine-tuning machine learning algorithms tools for quality control, and validating new features in collaboration with internal and external stakeholders 
Configure and maintain database servers and processes, including monitoring of system health and performance, to ensure high levels of performance, availability, and security. 
Develop pipelines/solutions to interact with third party software to ensure patient neuropsychometry data is available and suitable for downstream analysis.
Apply data modelling techniques to ensure development and implementation support efforts meet integration and performance expectations 
Build appropriate and useful reporting deliverables 
Continuously scanning the scientific literature to identify new approaches tomachine learning applicationsthat can be implemented to improve our capabilities 

Working for our organisation

King’s College Hospital NHS Foundation Trust is one of the UK’s largest and busiest teaching Trusts with a turnover of £1 billion, million patient contacts a year and around 15,000 staff based across 5 main sites in South East London. The Trust provides a full range of local hospital services across its different sites, and specialist services from King’s College Hospital (KCH) sites at Denmark Hill in Camberwell and at the Princess Royal University Hospital (PRUH) site in Bromley. 


The trust-wide strategy Strong Roots, Global Reach is our Vision to be BOLD, Brilliant people, Outstanding care, Leaders in Research, Innovation and Education, Diversity, Equality and Inclusion (EDI) at the heart of everything we do. By being person-centred, digitally-enabled, and focused on sustainability, we can take Team King’s to another level


King’s is dedicated to embracing the broad diversity of our staff, patients and communities and stand firmly against all forms of prejudice and discrimination. This includes, but is not limited to, racism, ableism, homophobia, biphobia, transphobia, sexism, ageism, religious discrimination, and any other prejudiced behaviour that undermines the rights, wellbeing and identity of our staff, and patients. 

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - New

Data Scientist - Imaging - Remote - Outside IR35

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.

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.