Summary
Jonathan Lacanlale is an Analytics Engineer with nine years of experience applying computer science and mathematics to turn messy data into actionable insights for nonprofits and consumer-facing products. He combines hands-on skills in Python, SQL, Looker, Tableau and ETL orchestration with a research background that produced multiple peer-reviewed publications in data-driven interfaces and AutoML benchmarking. Jonathan has built production ETL pipelines, automated data-quality monitoring in Argo workflows, and developed high-accuracy computer vision and NLP models during academic research—work that led to datasets, tooling, and conference presentations. Now based in Los Angeles and pursuing an MS in Data Science at UT Austin, he brings both product-minded engineering and reproducible research practices to cross-functional teams. An underrated strength is his history of translating research prototypes into production-ready systems, mentoring juniors and documenting workflows to ensure long-term maintainability.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Data Science, Master of Science - MS, Data Science at The University of Texas at Austin
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at California State University, Northridge