About me

Career, roles, and education

I'm Guillermo Leale, PhD in Engineering from Universidad Tecnológica Nacional (UTN). With more than two decades in the data field, my career has developed at the intersection of academia, industry, and consulting.

My work focuses on turning data into actionable knowledge. I've designed and built Business Intelligence solutions, Machine Learning models, and AI strategies for organizations in agribusiness, insurance, fintech, and space research. I collaborated with NASA Harvest on field-scale crop yield prediction models for Argentina, integrated into SIMA's platform.

I believe in the power of data to drive better decisions, and in training the next generation of professionals in the field.

Current roles

End-to-end Data-driven Projects Specialist

Data architecture, processing, and analytics

Full Professor

UTN, Facultad Regional Rosario

Independent Consultant

BI, Data Science & AI

Notable previous experience

Head of Data Management — Zur Analytics (2023–2025)

Data Science Consultant — SIMA Agtech, La Segunda Seguros, La Mutual de AMR (2019–2024)

Data Lead — REWORTH, Mexico (remote) (2022–2023)

Full Professor — Universidad Austral, School of Business Sciences, Rosario campus (2019–2023)

Academic Secretary — Universidad Abierta Interamericana (UAI) (2018–2021)

Postdoctoral Researcher — CONICET (2017–2018)

Education

PhD in Engineering (Information Systems) — UTN, Facultad Regional Santa Fe (2012–2017)

Information Systems Engineer — UTN, Facultad Regional Rosario (2000–2006)

Certifications

Snowflake SnowPro Core Certified

Snowflake Inc.

Software registrations

Three data automation tools registered with Argentina's National Copyright Office, DNDA (2019): Buscar Links Rotos, Buscar Títulos Facebook, and Buscar en Portales Diarios.

University teaching

20 years of university teaching: faculty at UTN Rosario since 2006 and Full Professor since 2019. Founder of the Master's in Data Mining, which I directed until 2025.

Academic committee member and reviewer for CoNaIISI and JAIIO (Argentine Symposiums on Technology and Society, Computer Science Education, and Engineering Education).

Research and publications

Research areas: machine learning, data science, bioinformatics, simulation and modeling, and STEM education. My work has been cited more than 50 times on Google Scholar.

  • Leale, G., Bayá, A.E., Milone, D.H., Granitto, P.M., Stegmayer, G. (2018). Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(1), 168–180.
  • Leale, G., Bayá, A.E., Milone, D.H., Granitto, P.M., Stegmayer, G. (2014). A novel clustering approach for biological data using a new distance based on Gene Ontology. ISCB-LA, IV International Society for Computational Biology Latin America, Buenos Aires.
  • Leale, G. (2018). Anatomía, Fisiología y Patología del Big Data: Reflexiones informático-clínicas en tres tomos. Revista Abierta de Informática Aplicada, 2(1), 39–46.
  • Castaño, E., Leale, G. (2020). Using Hybrid Bayesian Networks to Detect Audience Behaviour Changes in YouTube. European Modeling and Simulation Symposium (EMSS 2020).
  • Collaboration with NASA Harvest, University of Maryland, SIMA: Using Machine-Learning Models for Field-Scale Crop Yield and Condition Modeling in Argentina. Operational project since 2020.