About
Actuary & data scientist · UNAM
Andrés González Ortega is an actuary trained at UNAM's Facultad de Ciencias who builds production actuarial and data-science tools. His work joins risk theory with real software: insurance models, reserve valuation, artificial-intelligence agents, and data platforms that solve concrete problems in the Mexican insurance sector.
Andrés González Ortega builds actuarial and analytical software that reaches production, not just a notebook. He has built pricing engines for major medical expense insurance on CNSF data, reserve-valuation systems under the LISF and CUSF regulatory framework, AI agents that reason over Mexican regulation with retrieval-augmented generation (RAG), and data platforms that process information in the cloud. Every project starts from a question he cannot yet answer and ends in something that works.
Andrés González Ortega works at the intersection of actuarial science, machine learning, and data engineering. On the actuarial side he applies risk models, pricing with generalized linear models, mortality projection with Lee-Carter, and reserve valuation under Solvency II, the LISF, and the CUSF. On the technical side he uses Python, data platforms on Google Cloud such as BigQuery, language models with retrieval-augmented generation (RAG), and, out of curiosity, he trained a transformer on the work of Proust to understand attention mechanisms from the inside.
Andrés González Ortega studied Actuarial Science at the Facultad de Ciencias of the Universidad Nacional Autónoma de México (UNAM) and is currently completing his degree. That training gave him the foundations of probability, statistics, finance, and risk theory that every project in the portfolio rests on.
You can reach Andrés González Ortega by email at [email protected]. He is also on GitHub (https://github.com/GonorAndres) and LinkedIn (https://www.linkedin.com/in/andr%C3%A9s-g%C3%B3nzalez-ortega-190b49371/), where he shares his work and projects.