EXECUTIVE SUMMARY
Senior Data Scientist with a solid track record in applied and generative AI systems, leading large-scale data-driven transformations. Proven experience managing cross-functional teams and delivering high-impact solutions across industries such as finance, biotechnology, and supply chain. Skilled at bridging technical innovation and business strategy, delivering scalable architectures and data-driven decision intelligence systems for organizations including the Inter-American Development Bank (IADB), GDM Seeds, and Datup.
KEY PROJECTS & IMPACT
- Aurora (Inter-American Development Bank) via Globant: Leadership of Generative AI initiatives within Aurora, a RAG-based (LangChain) platform leveraging Azure and AWS. Directed bidirectional communication between the client (IADB) and Globant, aligning product strategy, backlog prioritization, and delivery across teams. Served as a strategic advisor to identify AI-driven opportunities and extend Aurora’s adoption across departments.
- MLOps Infrastructure for Genetic Modeling (GDM Seeds): Designed and deployed a Databricks-based MLOps architecture following medallion topology principles. Automated data ingestion, model training, and deployment using API Jobs, ensuring reproducibility and scalability. Led migration of statistical models from R to Python (Linear Mixed Models) for genetic crossbreeding optimization, enhancing operational efficiency across distributed teams.
- Supply Chain Forecasting (Datup): Developed and operationalized time series forecasting models (ARIMA, Exponential Smoothing, Deep Learning) to predict demand and supply stability. Built AWS-based data pipelines (Glue, Crawler, Athena, Quicksight, Sagemaker, EMR, among others) and implemented medallion architecture principles. Contributed across all CRISP-DM stages, from business understanding to production deployment.
