Our Mission

To prepare actuaries for Exam PA while equipping them with the skills needed to thrive in the modern world of data science.

Our Story

Six months ago, a colleague and I were sitting in an empty conference room on a Friday. It was three weeks before Exam PA. Our consensus was that there were not enough practice problems to work on. Both of us had been through the modules twice, and still had lots of questions. We teamed up by combining our study notes and quizzing each other. A few weeks later, we both passed with flying colors. Then only a few weeks later, two coworkers who were taking Exam PA in December also asked me if I had any notes, and at this point I realized that many people could benefit from more materials.

Data science tools, documentation, and training resources (Kaggle, Coursera, Udemy, AI for everyone, etc) have advanced rapidly over the last few years, but there is still a high demand for these resources within actuarial science. The way that data scientists learn machine learning, and how I learned at first, was not by taking an exam but by doing lots and lots of examples: kaggle competitions, data science interview projects, reading textbooks, and watching tutorial videos. This is a different style than the usual actuarial study method of buying a single study manual and then reading it from front-to-back. The goal of exampa.net is to give everyone access to this style of learning.

Our Team

Sam Castillo is a predictive modeler at Milliman in Chicago, maintains a blog about the future of risk, and won the 2019 SOA Predictive Analytics and Fururism’s Jupyter contest.

Willard Moore is an Owner/Developer at W3 Innovations, an IT consulting firm providing networking monitoring services. Before this he was a Research Analyst at Netflix.


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