Quality and reporting
Reliable national outputs
Quality assurance of national reports, dashboards, pre-release analytical outputs and webinar materials, with close attention to data integrity and methodological consistency.
About me
Data, evidence and technology for better decisions.
I am Imonikhe Ayeni, MBCS, AphA, a Principal Insight Analyst, Data Scientist and Researcher with more than seven years of analytics experience across healthcare, academic research and financial services. I work across statistical analysis, machine learning, deep learning, business intelligence, geospatial analytics, automation and reproducible reporting, with a strong focus on turning complex evidence into practical insight.
7+ years
Analytics experience
NHS
National patient experience analytics
MSc
Data Science with Distinction
MBCS, AphA
Professional memberships
My focus
Where analytics meets real-world impact
My career has moved across banking, university research and national healthcare analytics. The sectors are different, but the underlying challenge is often the same: turn imperfect and complex data into evidence that people can understand, trust and use.
I currently work as a Principal Insight Analyst at NHS Arden & GEM Commissioning Support Unit, contributing to analytical delivery across national patient experience survey programmes. Alongside this, I am a Research Assistant at Cardiff Metropolitan University, supporting multidisciplinary research involving artificial intelligence, public health, climate resilience, digital inclusion and intelligent technologies.
I am most interested in work that combines analytical rigour, reproducibility and clear communication, especially where the evidence can improve healthcare, public services, research or decision-making.
Healthcare analytics
From national survey data to deeper patient insight
At NHS Arden & GEM, I work extensively with the National Cancer Patient Experience Survey and the Under 16 Cancer Patient Experience Survey. My role combines analytical delivery with quality assurance, code improvement, automation and exploratory analysis that goes beyond standard reporting.
Additional insight
Beyond standard reporting
Subgroup feasibility, inequalities, regional analysis, key driver analysis, response-rate analysis and comparisons of online and paper survey responses.
Automation
Reproducible analytical workflows
Improving R code structure, repointing scripts and datasets, automating outputs and strengthening repeatable processes across survey programmes.
Exploration
New analytical questions
Exploring geography, demographic differences, qualitative evidence, intersectionality and appropriate machine learning approaches to uncover patterns that routine reporting may not reveal.
- Built and maintained geospatial and regional analytical pipelines for CPES and U16CPES.
- Delivered key driver analysis and high-level insight outputs for U16CPES.
- Developed response-rate reporting workflows and contributed to GPPS analytical function work.
- Supported qualitative analysis across cancer and maternity survey programmes.
- Contributed to dataset onboarding, testing and reproducibility work as analytical processes moved to new environments.
Applied research
Multidisciplinary research across technology, health and society
Climate resilience
Climate vulnerability and technology access in Morocco
I have supported research mapping climate vulnerability hotspots, examining gender-differentiated risks, assessing technology access gaps and considering how these patterns intersect with research capacity.
Food safety and public health
Intelligent technology for hand hygiene
I contributed as a Research Assistant to a multidisciplinary project exploring smart sensing and intelligent technology to support hand hygiene and food safety at home, including research support, data preparation, analysis and system-related work.
Digital inclusion
Digital Technology Learning Support Network
I supported data processing, statistical analysis and visualisation for research into digital skills, technology use and inclusion in Wales.
Research delivery
From raw data to publication-ready evidence
My research work has involved literature review, ETL, quantitative and qualitative analysis, system testing, visualisation, article support and preparation of evidence for academic and policy audiences.
Experience
A career built across analytics, research and decision support
Principal Insight Analyst
NHS Arden & GEM Commissioning Support Unit
2025 to present
National patient experience analytics covering CPES and U16CPES, quality assurance, subgroup feasibility, reporting automation, geospatial analysis, reproducibility and stakeholder-focused insight.
Research Assistant
Cardiff Metropolitan University
2023 to present
Applied data science and research across machine learning, statistical modelling, data engineering, climate resilience, digital inclusion, public health and intelligent technology.
Customer Service Advisor, Data Focus
Link Financial Outsourcing
2024 to 2025
Customer data management, payment pattern analysis, loan performance insight and analytical problem solving within a regulated financial services environment.
Business Intelligence Analyst
Access Bank Plc
2019 to 2023
SQL and Python analytics, dashboards, KPI development, loan and risk asset analysis, pricing insight, campaign evaluation and A/B testing.
Customer Experience Analyst
Diamond Bank Plc
2014 to 2019
Customer and transaction analytics, segmentation, targeted campaigns, data mining, reporting and decision support using SQL, Excel and relational data systems.
Selected technical projects
Applied data science from modelling to deployment
Healthcare machine learning
Stroke Risk Prediction
Developed and deployed a machine learning application for stroke risk prediction, comparing multiple supervised learning approaches and integrating the selected model into a Flask web application.
Predictive modelling
Airbnb Pricing
Built and compared Ridge Regression and Random Forest models using exploratory analysis, preprocessing and feature engineering to investigate rental price drivers.
Time series
Stock Volatility Forecasting
Applied GARCH and EGARCH models to Microsoft and Apple market data to examine volatility clustering, persistence and asymmetric responses to market shocks.
NLP and spatial analysis
Text and Geospatial Analytics
Applied natural language processing, sentiment analysis and geospatial methods to investigate patterns in textual and location-based datasets and communicate their practical implications.
Technical toolkit
Tools selected for the problem, not the other way around
Programming
Analytics and ML
BI and reporting
Cloud and data
Research
Education and credentials
Continuous learning backed by practical delivery
MSc Data Science, Distinction
Cardiff Metropolitan University, United Kingdom
MSc Geography and Planning
University of Lagos, Nigeria
BSc Geography and Regional Planning
University of Benin, Nigeria
MBCS and AphA
Professional Member of the British Computer Society and the Association of Professional Healthcare Analysts
Professional certifications include AWS Machine Learning Engineer, Microsoft Power BI Data Analyst, Oracle Data Science Professional, IBM watsonx Data Scientist, Azure AI Fundamentals, Snowflake and other cloud and AI credentials.
Knowledge sharing
Making technical learning easier to navigate
I enjoy explaining technical ideas as much as applying them. That interest led me to build a free Learning Library on this website, bringing together practical guides for people developing skills in programming, analytics and data science.
The current library includes structured resources for Python for Data Science, Machine Learning and AI, R for Data Science, Statistics and Reporting, and SQL for Data Analysis and Reporting. The aim is to combine syntax, explanation and practical examples in one place.
How I work
Four principles that guide my analytical work
Understand the question
Start with the decision, research question or operational problem before choosing a method.
Protect data quality
Validate inputs, assumptions and outputs so conclusions are supported by reliable evidence.
Build reproducibly
Automate repeatable work and structure analysis so it can be tested, reviewed and reused.
Communicate clearly
Translate technical findings into useful insight for both specialist and non-technical audiences.
Connect
Interested in my work?
I am always happy to connect around healthcare analytics, applied research, data science, business intelligence, cloud analytics and collaborative technical projects.