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Available now · full-time, part-time, remote & permanent roles in the Netherlands

Gabriel Nnana

Data Analyst · Business Intelligence · Healthcare Analytics

I turn messy healthcare and business data into decisions people act on.

5+ years across healthcare and business operations, a clinical biochemistry background, and an MBA in Data Analytics & AI in progress at Wittenborg University of Applied Sciences.

Gabriel Nnana
Based inAmsterdam, NL
~20%

lower average patient waiting time after a clinic adopted my ED staffing recommendations

1,981

data inconsistencies corrected across 12,000+ healthcare operational records

16 → 5 h

weekly performance review prep, cut by Power BI dashboards I built

251

maternity records analysed with chi-square and z-tests in a CRISP-DM gestational diabetes study

Studied and worked at

University of Westminster logoLondon · MSc and Clinical Data Coordinator
Wittenborg University of Applied Sciences logoNetherlands · MBA, Data Analytics & AI

What I do

From raw records to a decision you can defend.

Healthcare analytics

ED waiting time and staffing, bed occupancy, readmission risk and clinical research data, read by someone with a biomedical background.

BI & reporting

Power BI, DAX, Power Query and Excel dashboards that replace paper records and manual reports with live KPIs.

Data quality & prediction

Validation rules and cleaning that make the numbers reliable, then regression, machine learning and SHAP to show what drives them.

Selected work

Case studies

Each project follows CRISP-DM. It starts with the business question, goes through data quality, and ends with a recommendation someone can act on. Open any project for the full story.

ED performance executive KPI dashboard in Excel showing wait time, breach rate, weekday vs weekend staffing and trend
ED performance KPI dashboard: average wait 95.5 min. Weekends breached the 90-minute target on 100% of days vs 45% on weekdays.

Healthcare · Client work

Emergency department waiting time & staffing

~20%lower average waiting time after management adopted my staffing recommendations

Regression analysis at Carudo Clinic Center found a 118-minute peak wait and a 25% emergency case threshold driving delays. Weekends ran on 3 doctors against 3.6 on weekdays.

Power BIExcelRegressionCRISP-DM
30-day readmission risk KPI dashboard with risk-tier distribution and readmission rate by diagnosis
Risk-tiered KPI dashboard: 175 admissions, 30.3% readmission rate. Respiratory conditions led readmissions by diagnosis.

Healthcare · Predictive analytics

30-day hospital readmission risk

48% vs 3%actual readmission in the high-risk tier vs the low-risk tier

A full pipeline comparing Logistic Regression, Random Forest and XGBoost on ROC-AUC, PR-AUC, recall and calibration, with SHAP explaining each patient's score for discharge planning.

Pythonscikit-learnXGBoostSHAPPower BI
1-minute demo walkthrough. Interactive Power BI report: Administration had the largest share of leavers (37%). Laboratory Technicians had the most leavers by role (59).

HR · Business intelligence

HR attrition analytics

3×attrition among overtime workers (31.1% vs 10.2%), validated with chi-square tests

A 1,403 employee dataset modelled in Power Query with DAX KPIs. 43% of leavers exited within two years, which points retention work at early tenure onboarding and workload.

Power BIDAXPower QueryStatistics
Retail sales executive KPI dashboard showing revenue by category, gender, age band and weekday
Executive KPI dashboard over 1,000 transactions: Electronics was the top category and Saturday the strongest trading day.

Retail · Analytics workbook

Retail sales KPI dashboard

$456Krevenue analysed from descriptive through to prescriptive

Hypothesis testing across gender, category, age and day type. I caught a data truncation error that would have shown a false declining revenue trend before it reached stakeholders.

ExcelHypothesis testingDAX & SQL guide

Founder & team lead · 2026

NestNL

Arrive · Settle · Thrive

When I arrived in the Netherlands for my MBA, everything a new international student needs to know was scattered across dozens of search results. So I built the thing I wished I'd had.

NestNL guides students through their first 30 days in 18 steps: municipality registration, BSN, the residence permit card, a bank account, housing and GP registration, plus a campus hub, Scam Shield and optional premium support.

Problem to product

Brought the business problem and built the web app myself

Led a team of 5

International students from Nigeria, Iran and India

Pitched to Wittenborg

Proposed as a university partnership, under review

Launch focus

Amsterdam and Apeldoorn first, then wider NL

Visit nestnl.floot.app

With thanks to Dr Cansu Kadioglu, my Marketing Management lecturer at Wittenborg and one of the inspirations behind NestNL.

NestNL home screen showing Wittenborg Apeldoorn, the Arrive, Settle and Thrive stages, and progress across 18 steps
The live NestNL home screen

Testimonials

What people say about my work

You turned our healthcare data into actionable insights, helping us identify opportunities to improve patient waiting time and strengthen financial control.
Dr AnaikotDr AnaikotCarudo Clinic Center
Bravo! You demonstrated strong research skills, with an analytical approach to investigating complex problems.
Prof ItaProf ItaAkwa Ibom State University
I approach challenges logically, look for practical solutions, and focus on getting the job delivered on time.
JefferyJefferyDe Aftermath Consultancy Firm

Experience

Where I've done the work

Nov 2025 to present · Remote

Healthcare Data Analyst (Freelance)

Carudo Clinic Center, Uyo · Enlightir Global

Built Power BI and Excel dashboards for emergency department capacity planning, with a regression-based wait-time model, staffing rule analysis and scenario planning that replaced paper records. Staffing recommendations adopted by management cut average waiting time by ~20%. Cleaned and validated 12,000+ operational records, correcting 1,981 inconsistencies, and built Power BI dashboards that cut weekly review preparation from 16 to 5 hours. Led a CRISP-DM analysis of a gestational diabetes screening dataset.

Sep 2023 to Apr 2025

Healthcare Data Analyst & Clinical Data Coordinator

University of Westminster · London

Analysed laboratory and clinical datasets with SQL, Excel, Power BI and Python, including 374+ records for a potassium ion and atrial fibrillation research study. Built dashboards for clinical trends, ran ETL and validation checks, and supported 11+ master’s and 2 PhD students with statistical analysis.

Sep 2022 to Nov 2024

Data Quality Analyst

De Aftermath Consultancy Firm

Cleaned and validated data across 25+ client projects, catching duplicate records, gaps and inconsistencies. Designed standard validation rules and cleaning processes that reduced manual checking and correction by ~25%.

Dec 2017 to present

Founder

Datijeh Nigeria Limited

Founded and lead a workforce, recruitment and operations consultancy (30+ client projects a year, team of 34). Manage an annual budget of ~$450K, calculate IRR and EVA for investment decisions, and moved reporting from paper to digital across 11+ locations, including a weekly P&L for each location.

Toolkit

Power BIDAXPower Query (M)SQLExcel (advanced)Python · pandas · scikit-learnSHAPSPSSRegression & hypothesis testingCRISP-DM

Education

MBA, Data Analytics & AI
Wittenborg University of Applied Sciences · Jul 2026 to Feb 2028 (in progress)
MSc Biomedical Sciences (Clinical Biochemistry)
University of Westminster, London · Sep 2023 to Mar 2025
MSc Biological Sciences
Akwa Ibom State University · Oct 2020 to Feb 2023
BSc Biological Sciences
University of Calabar · Nov 2009 to Aug 2015

Certifications

Google Data Analytics Certificate
2026
Model Context Protocol
Anthropic Academy · 2026
Microsoft PL-300 (Power BI Data Analyst)
In progress · expected November 2026
Languages
English (fluent) · Dutch (learning)