Summary
Field Cady is a data engineer and applied-math researcher with 11+ years of experience building production analytics and machine learning systems for startups, nonprofits, and major enterprises. He blends a hacker’s mentality with rigorous probabilistic modeling—shipping Python-first prototypes that scale into production code in C++ and Scala when needed. His work ranges from redesigning SciPy’s interpolation module and inventing a continuous-time HMM Python package to leading analytics at Semantic Scholar and building task-mining algorithms at Zeitworks. As a consultant he helps organizations adopt data science best practices and has driven measurable business impact, including a 50x cost reduction in testing frameworks at Walgreens. He’s also an author of two Wiley books and several public projects (including tools to map overstocked alpine lakes) that reflect a taste for practical, broadly useful research. Based in Edmonds, WA, he currently applies his metadata expertise at Meta while continuing independent consulting and open-source development.
11 years of coding experience
14 years of employment as a software developer
M.S. Applied Mathematics, M.S. Applied Mathematics at University of Washington
High School Diploma, High School Diploma at Klahowya Secondary School
MS (PhD Dropout) Computer Science, MS (PhD Dropout) Computer Science at Carnegie Mellon University
B.S. Physics Mathematics, B.S. Physics Mathematics at Stanford University
English, Spanish, Chinese