Summary
Daniel Cañas is a Staff Software Engineer based in New York with 13 years of experience building predictive analytics and real-time data systems that turn large-scale data into commercial value. He has led end-to-end projects from CRISP-DM-driven modeling to production integration—delivering churn prediction, lifetime value, segmentation, and fraud-detection pipelines for telecom and banking clients. Comfortable across Java, Python, functional languages and big-data stacks, Daniel has a track record of reducing costs and complexity by replacing vendor components and enabling real-time lookups for decisioning engines. He combines hands-on implementation (Hadoop prototypes, JVM model integration, Neo4J) with engineering leadership roles that introduced CI, agile tooling, and deployable services. An adjunct professor and former research assistant, he pairs practical product delivery with a strong academic grounding in clustering and data science.
13 years of coding experience
19 years of employment as a software developer
MS, Computer Science, MS, Computer Science at North Carolina State University
BS, Computer Science, BS, Computer Science at Wake Forest University
English, Spanish