Quantitative Advisory
DataMetricus provides independent statistical and actuarial modelling, applied health metrics, and reproducible research workflows for institutions where analytical quality is non-negotiable.
Each engagement is scoped, documented, and delivered to institutional standards.
Structured mortality, morbidity, and reserving models built for audit. Outputs documented to regulatory and internal governance standards.
Epidemiological and population health analyses using validated frameworks. Results traceable from source data through to reported estimates.
End-to-end analytical pipelines in R, Python, and Quarto. Version-controlled, tested, and structured so any qualified analyst can audit the chain of reasoning.
Structured programmes for analysts and research teams. Foundations through to applied modelling and reproducible workflow practice.
Every deliverable is structured so that results can be independently verified. Code is version-controlled and documented. Assumptions are stated explicitly and tested against alternatives. Data provenance is recorded at every transformation step.
We do not produce black-box outputs. Clients receive not only findings but the documented analytical chain that produced them — enabling internal review, regulatory examination, or downstream use by their own teams.
All outputs carry a documented audit trail from raw input to final result.
No manual steps without documentation. Pipelines are scripted, not assembled by hand.
Sensitivity analyses accompany every primary estimate. Uncertainty is quantified, not suppressed.
Analytical conclusions are not adjusted for client preference. Findings are reported as the data supports.
Selected outcomes from completed projects. Client details withheld by agreement.
Reviewed and updated best-estimate mortality assumptions for a life insurer's annuity book. Delivered a fully documented R pipeline, enabling the client's actuarial team to re-run and audit the analysis independently.
Constructed reproducible DALY estimates for a regional health authority using linked administrative datasets. Methodology report prepared to academic publication standard with full sensitivity analysis.
Assessed reproducibility and traceability of statistical outputs produced by an internal analytics team. Delivered a structured recommendations report with annotated code examples.
Migrated a multi-analyst epidemiological study from disconnected scripts to a Quarto-based reproducible pipeline with Git versioning, shared data contracts, and automated output checks.