Summary
Andrew Tilley is a Principal Data Scientist based in Denver with 11–12 years building production-grade data products and machine learning systems for consumer and financial brands. He combines hands-on engineering—writing production R and Python, PySpark pipelines, Airflow orchestration, and xgboost models—with product-minded delivery, having led teams and embedded as a consultant to ship novel data products like Spring Labs’ Income Stability Indicators. His background spans end-to-end ML work from experimentation and continuous validation of recommenders to operational algorithms for delivery logistics and automated shift planning. He has run his own consulting business, managing client relationships and the full operational stack from invoicing to deployment, and has experience presenting complex analytics directly to enterprise clients. Known for bridging research-quality modeling and pragmatic production practices, he emphasizes robust testing, monitoring, and business-aligned metrics. Trained in computational and applied mathematics and statistics at Rice University, he pairs rigorous quantitative foundations with years of real-world ML engineering.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Arts (B.A.), Computational and Applied Mathematics, Statistics, Bachelor of Arts (B.A.), Computational and Applied Mathematics, Statistics at Rice University