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Welcome to Paul Martin McNeill's portfolio. Paul is an AI engineer, web developer and data analyst on the island of Ireland, with over fifteen years across IT, data and engineering. He builds tools for care, communication and everyday work: Voice, a predictive communication app for people who cannot rely on speech; analytics for health and social care; and reproducible machine learning research on public data. He holds a master's in Artificial Intelligence from Queen's University Belfast, and a First-Class degree in Computing from The Open University. Every project here has a case study, and several run live in your browser. To talk about a role or a project, use Get in touch.
Narrated with an AI voice made with ElevenLabs. It is not Paul’s voice.
15+ yearsacross IT, data and engineering
Master’s in Artificial IntelligenceQueen’s University Belfast
First-Class BSc (Hons)Computing, The Open University
Inside the system
Care data, connected.
Follow a care record from source tables to an operational dashboard.
Step 1 of 3
Source records
Client records, visits, runs and rotas, workforce and finance data form the source layer. Aurora uses a synthetic dataset to demonstrate a Northern Ireland care model.
Step 2 of 3
Transform & model
Power Query cleans and prepares the tables. The data model connects them, while DAX measures turn visit and finance records into reportable indicators.
Step 3 of 3
Operational insight
Dashboards bring together missed visits, workforce, finance and compliance, with locality views and mobile layouts.
Each answer below is a measured result from two studies on public data, with the method, the failures and the corrections published beside it.
Is the result real?
0.14 R² from noise
Choosing a model's inputs before testing it scored 0.14 on shuffled data with nothing to find. That is as high as the real result. Done in the right order, the same recipe scored below zero.
Three and seven days ahead, 75 to 80% of the model's high-river warnings were wrong. A band drawn around today's flow, with no model at all, came close: 0.155 against 0.175 on the same score at seven days.
A forecasting model trained on wet catchments and tested on dry ones lost about 0.10 of its skill, against 0.03 for a control trained on a random half. A whole region held out of training cost 0.019.
Refit the same model on a slightly different sample and its list of the 20 most important inputs changes. On average two refits share about a third of their lists (an overlap score of 0.20). Only two inputs stayed near the top.
I’m Paul, an AI engineer, web developer and data analyst based on the island of Ireland.
I build LLM-powered tools, web platforms and analytics
for healthcare, accessibility and day-to-day operations.
My recent work includes NHSCT-aligned digital transformation,
with Power BI reporting for care operations and compliance, and
AI accessibility tools such as a predictive AAC app for non-verbal users.
I hold a master’s in Artificial Intelligence from Queen’s University Belfast
and a First-Class BSc (Hons) in Computing from The Open University.
I’ve also completed the Open University’s postgraduate M816 Data Management module.
Paul took our domiciliary care reporting from scattered Excel files and manual processes to a fully automated Power BI suite. What used to take the team days now takes minutes. He understood the clinical context, not just the data — that's rare.
Dr. Claire HendronService Manager, Domiciliary CareNorthern Health & Social Care Trust
We needed someone who could handle the full picture — data modelling, ETL pipelines, DAX, and the front-end dashboards — and explain it all to non-technical stakeholders. Paul delivered on every front.
Gareth MurrayHead of Digital ServicesNHSCT
The AAC app Paul built changed how we think about assistive technology. The AI prediction engine was fast, accurate, and most importantly, the families found it intuitive. That last part is the hardest to get right.
Dr. Aisling O'KaneSpeech & Language TherapistHSC Northern Ireland
Get in touch
Have something worth building?
Currently open to AI engineering, ML, and full-stack web opportunities — full-time, contract, or freelance.
Tell me about the role or project, what you need built and your timeline.
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