Principal Insight Analyst · Data Scientist

Imonikhe Ayeni, MBCS, AphA

AWS Certified Machine Learning Engineer · Oracle Certified Data Science Professional · Microsoft Certified Power BI Data Analyst · IBM Certified Data Scientist · Snowflake Certified · Healthcare Analytics Specialist

+44 7901 364528 imonikheayeni@gmail.com United Kingdom LinkedIn GitHub Website
Portrait of Imonikhe Ayeni

Professional Profile

Data scientist and analyst with 7+ years of experience delivering machine learning, business intelligence and analytics solutions across healthcare, finance and academic research. Holds an MSc in Data Science with Distinction from Cardiff Metropolitan University and multiple industry certifications including AWS Machine Learning Engineer Associate and Oracle Data Science Professional. Proficient in Python, SQL, R and cloud platforms including Azure, AWS, Databricks and Snowflake, with hands-on experience building and deploying predictive models, managing databases and creating interactive dashboards. Currently contributing to national research and NHS analytics projects involving machine learning, statistical modelling and data engineering, with experience mentoring junior analysts and communicating complex concepts to non-technical audiences.

Professional Experience

Principal Insight Analyst

NHS Arden & GEM Commissioning Support Unit · Leicester, United Kingdom
09/2025 – Present
  • Lead analytical delivery for the national NHSE Cancer Patient Experience Survey (CPES and U16CPES) programme, turning complex qualitative and quantitative patient data into actionable insights that shape policy, clinical practice and operational decisions.
  • Delivered end-to-end quality assurance for the U16CPES 2024 national dashboard and report, including pre-release briefing data packs, ensuring data integrity and methodological rigour.
  • Designed and executed subgroup feasibility analyses covering patient class, long-term conditions, treatment type, ethnicity and English as a first language to explore enhanced reporting options and uncover deeper patient experience patterns.
  • Built and maintained geospatial and regional analysis pipelines for U16CPES and CPES, including public sharing versions that highlight location-based trends.
  • Automated reporting and qualitative workflows by repointing R scripts, transferring person-level datasets, optimising code for UDAL and creating Excel automation tools to improve efficiency and reproducibility.
  • Conducted key driver analysis, response rate markdowns, maternity survey QDC analysis and presentation, pilot trust results, and supported GPPS function work while supervising junior analysts to meet tight deadlines.
  • Translate business and clinical requirements into robust analytical designs using Python, R, SQL, Power BI, Tableau and Databricks.

Research Assistant

Cardiff Metropolitan University · Cardiff, United Kingdom
05/2023 – Present
  • Delivered data engineering, statistical modelling and machine learning for national research projects including the Stroke Risk Prediction Model, Technology Driven Climate Resilience, Behavioural AI Systems for Food Safety, and Digital Skills and Inclusion in Wales.
  • Led data analysis, ETL processes and visualisation for the Digital Technology Learning Support Network project using Python, Power BI, Tableau, SQL and Azure Synapse.
  • Performed qualitative and quantitative analysis with NVivo, LaTeX, Python, SPSS, Tableau and Power BI to produce insights for academic publications and policy recommendations.

Customer Service Advisor (Data Focus)

Link Financial Outsourcing · Caerphilly, United Kingdom
09/2024 – 09/2025
  • Maintained accurate customer data records and executed data entry tasks in line with compliance and regulatory protocols, supporting data integrity for analytical purposes.
  • Analysed customer payment patterns and loan performance metrics to recommend data-driven repayment strategies tailored to individual financial profiles.
  • Used CRM platforms to track customer interactions and record updates, ensuring data consistency across databases for reliable reporting.
  • Applied analytical problem-solving to complex customer situations, delivering solutions for improved loan management and payment optimisation.

Business Intelligence Analyst

Access Bank Plc
04/2019 – 01/2023
  • Developed and maintained reports, dashboards and KPIs using SQL and Python, improving operational efficiency.
  • Built predictive models to analyse risk asset performance and optimise pricing strategies.
  • Implemented data-driven solutions to reduce loan delinquency, collaborating with stakeholders to develop action plans.
  • Conducted in-depth analysis of marketing campaigns using Python and SQL to evaluate ROI and customer impact.
  • Ran A/B testing for marketing campaigns, analysing statistical significance and ROI.

Customer Experience Analyst

Diamond Bank Plc
04/2014 – 03/2019
  • Transformed raw transaction data into meaningful insights using SQL and Excel.
  • Developed and executed micro-segmented marketing campaigns targeting dormant customers, increasing monthly revenue generation.
  • Used relational and statistical database management systems to perform data analytics and improve online marketing activities, achieving a productivity increase of over 90% through data mining, modelling and SQL scripting.
  • Applied customer segmentation models to profile usage patterns and tenure, enabling targeted offer mapping and personalised campaign strategies.
  • Collaborated with stakeholders to understand business requirements and translate them into analytical solutions.
  • Created data visualisation dashboards that improved decision-making processes.

Key Projects

Airbnb Predictive Pricing Model

Python · Random Forest · Ridge Regression

Developed machine learning models to predict Airbnb prices with 58.6% R² accuracy, using feature engineering and ensemble methods to optimise model performance.

Stock Volatility Analysis & Forecasting

Python · GARCH · EGARCH

Conducted comparative volatility analysis of Microsoft and Apple, validating GARCH and EGARCH models to demonstrate volatility clustering, persistence and leverage effects.

Stroke Risk Prediction Model

Python · Machine Learning · Flask · Heroku

Built and deployed a stroke risk prediction model with an automated model retraining pipeline and interactive user interface.

Geospatial Machine Learning

Python · Geospatial Libraries

Implemented spatial clustering algorithms to analyse geographic patterns and uncover location-based trends for strategic decision-making.