Summary
Jason Kroll is an applied scientist with 12 years of experience optimizing and modeling large distributed systems, currently driving DynamoDB performance at AWS in Seattle. He combines a strong academic foundation (MS in Computer Science, Tufts) with hands-on engineering across startups and enterprises, from building NLP-driven job-matching and crawling pipelines to migrating social platforms onto graph databases. His work blends statistical analysis, capacity planning, and production ML to squeeze performance and reveal actionable signals in noisy, large-scale data. Notably, he has built self-generating filtering systems and large-scale crawlers that tamed duplicate-heavy datasets—a skill set that informs his current focus on high-throughput database performance.
12 years of coding experience
8 years of employment as a software developer
BA, Economics, BA, Economics at University of Washington
MS, Computer Science, MS, Computer Science at Tufts University
Russian, Finnish