Summary
Skyler Roh is a software engineer specializing in machine learning platforms with 11 years of experience building production ML and data solutions for advertising, retail personalization, and SaaS analytics. He has driven ML platform work at DoorDash and Iterable and previously delivered real-time bidding models and production pipelines at Adobe, bridging data science research and large-scale engineering. A UC Berkeley graduate with an MS in Information and Data Science, Skyler combines strong statistical foundations with hands-on Spark/Scala and Python engineering to operationalize models and automate feature pipelines. He’s proven at increasing data coverage and efficiency—e.g., a fuzzy-matching initiative that grew profile coverage by 40% and reporting automations that halved reporting time—and enjoys applying analytical curiosity from public health to commercial ML problems. Outside of work he pursues photography, videography, and competitive athletics, which inform his attention to detail and iterative improvement mindset.
11 years of coding experience
8 years of employment as a software developer
B.A. Statistics, B.A. Statistics at University of California, Berkeley
Master of Science - MS Information and Data Science, Master of Science - MS Information and Data Science at UC Berkeley School of Information
English, French