For Clients / Data Analytics
Quantitative modelling, data engineering and predictive analytics for insurance actuarial work. Python, R, SQL, cloud data platforms and modern ML toolchains supported. We build, clean and analyse; your actuaries interpret and sign off.
Scope
End-to-end pipeline design from source system to actuarial model input, with data quality checks built in.
Data profiling, quality rule design, reconciliation workflows and audit-trail preparation.
GLMs, tree-based models, gradient boosting and neural networks applied to pricing, retention and claims problems.
Automation of recurring analytical work, moving Excel processes into reproducible code with version control.
Interactive dashboards, management reporting and analytical decks that make actuarial output useful across the business.
AWS, Azure and GCP data platform work for actuarial teams looking to move off legacy tools.