My name is Marcos Aguilera Keyser. I started college as an Economist. Later I decided on becoming an actuary. After a year working in a traditional actuarial role I switched to SAS Institute.
SAS Institute was sponsoring my actuarial studies at that moment. So, I had the opportunity to taste a little of SAS programming and see how exiting could be thinks such “data mining” or “business intelligence”, the buzzwords ten years ago in the analytical world.
It was at SAS where I really learned about coding, statistical analysis, data mining and many other tech skills that one learns in an analytical software company: databases, ETL, server administration, software development, administration and installation or even big data. I’ve learned by doing through many projects in many different clients. But also, I received an unevaluable training from SAS through many courses in code, statistical analysis and data mining. Finally, I learned by teaching others in code, statistical analysis and data mining during years.
At SAS Institute, I worked in different national and international consulting projects, many times in partnership with Accenture, Deloitte, KPMG, etc. I devoted a lot of time working for Insurance companies. Working side-by-side with the actuaries in different areas, I was involved in different projects such actuarial pricing (ratemaking), price optimization, credit scoring, reserve modeling, client segmentation or text-mining (NLP). I became an expert in the generalized linear model (GLM) framework modeling the Frequency, Severity, Burning Cost, retention, etc. Also, I used a lot of data mining (machine learning) tools such as decision trees, SVM, ensembles, neural networks or text mining (NLP).
After six year at SAS learning how to build production-ready successful machine learning models, I wanted to learn more about business side of my analytical job. Therefore, I switched to an Insurance company, Liberty Mutual, where I spend more than 3 years involved in several cool projects. Finally, nowadays I am working in a start-up doing even more cool thinks with big data, deep learning, and cloud computing.