Built on patterns: How Susan Chang’s econometrics roots drive machine learning for security and her minimalist workspace

Susan Chang, a principal data scientist at Elastic's Security team, shares how her econometrics background shaped her approach to machine learning for cybersecurity. She builds ML systems that detect anomalous behavior in high-volume security data streams, including evaluation frameworks to measure model improvements and reduce false positives. The post also covers her minimalist desk setup and her advice for those entering security ML: build strong ML fundamentals first, then learn the domain.