Healthcare Audit Data Analyst

ROYAL COLLEGE OF PAEDIATRICS AND CHILD HEALTH
City of London
4 days ago
Create job alert

Healthcare Audit Data Analyst
£41,278 pa plus excellent benefits
London WC1 and home-based
35 hours per week, full-time
Fixed Term Contract to 31 March 2027 (potential extension to 31 March 2030)


The Royal College of Paediatrics and Child Health (RCPCH) is seeking a highly skilled Healthcare Audit Data Analyst to join our Research and Quality Improvement Directorate, which promotes evidence-based practice and improves health outcomes for children. This is an exciting opportunity to work on national audit programmes that shape paediatric care across the UK.


Reporting to the Project Manager (Audits), you will manage complex healthcare datasets, lead on data analysis using R/R Studio, and produce high-quality outputs for clinicians, commissioners, and policy makers. You'll play a key role in delivering robust, reproducible analytical pipelines and ensuring data integrity and security throughout the audit lifecycle.


Key responsibilities include:

  • Managing secure handling and analysis of complex audit datasets, ensuring compliance with data governance and protection requirements.
  • Developing reproducible analytical pipelines to underpin audit outputs and support cross-audit working.
  • Analysing large datasets using R/R Studio, producing results at unit, ICB, regional and national levels, and identifying trends and outliers.
  • Maintaining robust data management processes within GitHub environments for version control and collaboration.
  • Producing reports and data outputs for diverse audiences, including clinicians, commissioners, regulators, and patient stakeholders.
  • Acting as a point of contact for technical and data-related queries from those submitting data for analysis.
  • Planning analytical processes for upcoming projects and contributing to departmental reports, including interpretation and editorial content.
  • Supporting the development and enhancement of data capture software and collaborating with internal and external stakeholders.

Essential skills and experience:

  • Undergraduate degree or equivalent experience in social or medical science, statistics, or another numerate discipline.
  • Proven experience using R/R Studio (or VS Code) for data cleaning, aggregation, recoding, merging, and advanced analysis (including regression).
  • Experience producing high-quality written reports and documentation for varied audiences.
  • Strong understanding of data governance, security, and version control, including experience with GitHub.
  • Ability to manage and interrogate large, complex datasets and apply appropriate statistical methodologies.
  • Excellent interpersonal skills and ability to build relationships with healthcare professionals.
  • High level of numeracy, attention to detail, and accuracy.
  • Strong IT skills, particularly in MS Excel, Word, and PowerPoint.

Desirable:

  • Experience with Stata, SQL, or Python, and advanced Excel functions.
  • Familiarity with Power BI or Quarto for data visualisation and reporting.
  • Experience developing data export and dashboard reporting functions.
  • Understanding of NHS organisational structures and experience preparing data for commissioners and regulators.

The RCPCH has more than 25,000 members and fellows and employs around 200 staff, most of whom work in our London office in Holborn. We have a Devolved Nations team operating from Northern Ireland, Scotland and Wales. Our College values: Include, Influence, Innovate and Inspire, are important to us. These values ensure we bring out the best in each other, strive forward together to make the College a positive and dynamic place to work.


The RCPCH champions Equality, Diversity and Inclusion. Our workplace is inclusive, offering a supportive environment where staff can thrive. The College is keen to accept applications from people with protected characteristics. We believe that our staff should represent all of the diverse communities we serve. Join us to help realise our vision of a world where every child is healthy and well.


The College operates a flexible and modern working policy, whereby our colleagues work in the office for a minimum of 40% over a 4 week cycle and the remainder from home.


The RCPCH is committed to safeguarding the children, young people and adults it has contact with in the exercise of its functions and responsibilities. The RCPCH expects all staff to share this commitment - we place a high priority on ensuring only those who do so are recruited to work for us.


All offers of employment will be subject to satisfactory references and appropriate screening checks, which can include criminal records.


Closing date: 08 February 2026


We reserve the right to close this vacancy early if we receive sufficient applications for the role. Therefore, if you are interested, please submit your application as early as possible.


#J-18808-Ljbffr

Related Jobs

View all jobs

Healthcare Audit Data Analyst

Healthcare Audit Data Analyst

Healthcare Audit Data Analyst (Remote/London)

Healthcare Audit Data Analyst (Remote/Hybrid)

Senior Claims Data Analyst

Claims Data Analyst

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.