Recommendation System via Offline RL
Optimize your customer retention with intelligent agents that deliver precise recommendations by learning from your historical data.
Hello human
“Guided by the belief that, together, we can build better data and AI problem solutions that could enhance people’s lives.”
I'm an Applied Mathematician turned Data Scientist, with a M.Sc. in Data Science from ITAM — the top-ranked Data Science program in México. I specialize in delivering end-to-end data science solutions — from feature engineering and predictive modeling to scalable cloud deployment — translating complex data into actionable strategies that drive measurable business impact.
My work spans credit risk modeling, causal inference, deep learning (LSTM, transformers), classical ML (XGBoost, LightGBM), and data engineering on cloud platforms like AWS and Snowflake. I thrive at the intersection of mathematics, statistics, and business impact.
Experienced in delivering end-to-end data science solutions — from business problem understanding to data engineering, modeling, and scalable deployment — driving strategic decisions and optimizing KPIs across the retail and fintech industries.
Optimize your customer retention with intelligent agents that deliver precise recommendations by learning from your historical data.
Protect your brand and users by fine-tuning AI models to detect deceptive content and align with human-centric values.
Convert your natural language queries into executable SQL code without any worries about knowing SQL!
I'm always open to discussing new opportunities, interesting projects, or ways we can collaborate on data & AI challenges.