Summary
Arif Ali is a data scientist with 12 years of experience and a track record of turning one-off analyses into production-ready, reusable frameworks across advertising, healthcare, support, hardware, and fraud domains at Amazon. He founded experimentation science in Advertiser Experience, scaling experiments from 6 to 35 per year and inventing graph-based methods to handle spillover where standard A/B tests fail. His causal inference work validated nine-figure annual impacts and he built MLOps and batch NLP pipelines that cut runtimes from hours to minutes and automated classification of 300K weekly transcripts. Equally focused on methodology as outcomes, he raises organizational standards so analyses become enduring tools rather than forgotten reports. He enjoys building for technical users—enabling engineers, clinicians, and analysts to do things they couldn’t before—and mentors cross-functional teams on statistical best practices. Based in Seattle, he holds an MS in Data Science from Georgetown and a BA in Statistics from UC Berkeley.
12 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (B.A.), Statistics, Bachelor of Arts (B.A.), Statistics at University of California, Berkeley
Master of Science (M.S.), Data Science, Master of Science (M.S.), Data Science at Georgetown University
Gujarati, French, hindi-urdu, English