About

I am an actuarial consultant with strong experience in machine learning, mortality analysis, IFRS 17, and presenting training workshops & talks.

My background is in actuarial science. I have obtained 9 exemptions and I am registered as a TASSA.

I have been lucky enough to be on projects covering a wide breadth of tech, from web dev to Linux administration to cloud computing. This has helped me quickly pick up new frameworks and libraries depending on the project, and develop a solution that is tested, well-documented, and easily communicated back to clients.

This past year, I became an AWS Certified Cloud Practitioner and am preparing for AWS Solutions Architect Associate alongside Terraform Associate to produce well-architected, version controlled, and maintainable cloud infrastructure.

I am closely following the cloud native space and developing small projects on local clusters. I am keen to get more hands-on and involved in the community from the 2nd half ofthis year.

Lately, I have been fortunate enough to be involved in research projects using Bayesian modelling (turing.jl, GaussianProcesses.jl), analytical approximation (SymbolicRegression.jl), and fairness modelling (fairlearn) libraries. These approaches can produce models which are very flexible, communicate uncertainty, are more transparent, and can help protect marginalised groups against unfair outcomes.

In my sparetime, I like to work on personal projects, tinker with my dot files (Neovim, mainly - no WM yet :) ), and contribute back to open source projects where I can. I feel strongly about software that is open and freely accessible so all can benefit and learn from it.

Away from my desk, I enjoy reading, gymnastics, podcasts, and travelling.