Summary
Mark Secada is a Senior Data Scientist in New York with 11 years of experience applying ML and NLP to media and product problems, including multi-year roles at The Wall Street Journal, Dow Jones, and Tinder. He builds production-ready systems in Python, R, SQL and Node.js on Google Cloud, and has shipped classifiers and embedding-driven tools that saved newsroom teams weeks of manual work and improved moderation and audience modeling. His work at the WSJ includes leading doc2vec model selection, a breaking-news classifier, and a gender-diversity analyzer used editorially, and he co-authored a high-impact data-driven investigation cited in major coverage. Known for turning messy, high-volume text and audience data into practical analytics and production ML, he blends rigorous math training from NYU with strong engineering discipline.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Arts (B.A.) Mathematics, Bachelor of Arts (B.A.) Mathematics at New York University
English, Spanish