Data Analytics · Business Intelligence · Analytics Engineering · Applied Machine Learning
I build analytical systems that turn operational data into clear, measurable decisions using Power BI, Python, SQL, data modelling and machine learning.
Johannesburg, South Africa
Power BI · Analytics Engineering · Data Quality · SQL · Python
A source-controlled Power BI decision-support project built on 75,000 synthetic claims. The repository contains an editable PBIP/PBIR report, a TMDL semantic model, 79 explicit DAX measures, Power Query transformations, SQL analysis, a deterministic Python data pipeline, 8 report pages and 33 automated QA checks. GitHub Actions rebuilds and validates the project on every push and pull request.
View the flagship project · Review the QA workflow
Applied Machine Learning · Decision Science · Model Governance
A synthetic-data case study for capacity-constrained review prioritisation. The project compares classification approaches through a leakage-safe pipeline, stratified cross-validation, an untouched holdout set and ranking metrics at practical review capacities. It also examines model explainability, sensitive-feature governance and human oversight.
View the machine-learning project
Both repositories use synthetic data. Their analytical results are portfolio evidence, not employer results or production performance.
| Area | Tools and methods |
|---|---|
| Analytics and programming | Python · SQL · R · Excel |
| Business intelligence | Power BI · DAX · Power Query · Tableau |
| Data modelling and analytics engineering | Dimensional modelling · Semantic modelling · PBIP · PBIR · TMDL · Data quality |
| Machine learning | scikit-learn · XGBoost · Imbalanced classification · Model evaluation |
| Engineering and delivery | Git · GitHub · GitHub Actions · CI/CD · Testing |
My background combines business and operations experience with applied analytics. I work on data quality, performance measurement, process improvement, risk-aware decision support and communication for operational and executive audiences. Insurance and claims are established areas of domain knowledge, not the limit of my analytical work.
These outcomes relate to professional claims and operations work. They are separate from the synthetic portfolio results above.
| Area | Outcome |
|---|---|
| Claims handling | 40% faster following process redesign |
| Fraud identified or prevented | R500K+ |
| Claims managed | Approximately 200 motor and agricultural claims per month |
- Insurance Specialist, Old Mutual Insure (Oct 2023 to present)
- Claims Specialist, Auto & General Australia (Oct 2022 to Jun 2023)
- Customer Support Specialist, Bob Group (Oct 2021 to Sep 2022)
- Associate Claims Coordinator, Innovation Group South Africa (Sep 2018 to Aug 2020)
- Microsoft Certified: Azure Data Scientist Associate, issued Nov 2025, expires Nov 2026
- Microsoft Certified: Power BI Data Analyst Associate, issued Oct 2025
- Oracle Cloud Infrastructure 2025 Certified Data Science Professional, issued Jul 2025, expires Jul 2027
- Introduction to Data Analytics, TAFE NSW, issued Oct 2025
- Lean Six Sigma Black Belt
Credential links will be added only when the corresponding public verification URLs are available.
Senior Data Analyst · Data Analytics · Business Intelligence · Analytics Engineering · Operations Analytics · Decision Support · Data Science
Insurance analytics remains a secondary domain specialism.