Summary
Mauro Escudero is a Machine Learning Engineer in London with eight years of experience bridging academic research and production ML, currently building multilingual geopolitical intelligence systems at ExTrac. He holds a PhD in Computational Statistics and Data Science from the University of Bristol and spent a postdoc translating theory on generative diffusion models and scalable sampling into practical sampling algorithms. Mauro’s strengths span scalable sampling, generative models, variational inference and causal ML, with hands-on engineering in Python, R and Julia—he notably implemented a low-rank treatment effect model at Afiniti that beat prior approaches by an order of magnitude. At ExTrac he leads deployment of multilingual LLMs, high-throughput NER, synthetic data pipelines and an asynchronous CommsMapping service, while also shaping the team’s AI ethics strategy. He is motivated by tech-for-good applications—energy, environment and healthcare—and brings a rare combination of theoretical depth and production-grade systems design.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BSc) Bsc Hons Mathematics with YiE, Bachelor of Science (BSc) Bsc Hons Mathematics with YiE at University of Southampton
Diploma di Stato Scientifico Tradizionale, Diploma di Stato Scientifico Tradizionale at Liceo Scientifico Galileo Galilei
PhD Computational Statistics and Data Science (COMPASS) Statistics, PhD Computational Statistics and Data Science (COMPASS) Statistics at University of Bristol
Italian, English, Spanish, Latin