Marshall Krassenstein is a Solutions Architect with nine years of experience applying machine learning, interactive visualizations, and data pipeline engineering to real-world problems across healthcare, finance, and enterprise AI platforms. With an M.S. in Analytics from Georgia Tech, he has driven customer-facing and product development work at DataRobot—building developer tools like the datarobotx Python package and templated application pipelines—and now shapes data solutions at Databricks. He combines hands-on coding (Python, R, SQL) with customer engineering, having led proof-of-value engagements, built forecasting and feature-engineering systems for banks, and implemented large-scale public-health analyses for CDC and HHS. Marshall’s background includes optimizing high-throughput transaction queries and scraping/normalizing messy healthcare data, showing a talent for turning fragmented sources into production-ready analytics. Based in Pittsburgh, he’s equally known for pragmatic delivery and a willingness to prototype unusual ideas—when not thinking about smoothies and his dog.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS Analytics, Master of Science - MS Analytics at Georgia Institute of Technology
Bachelor of Arts (B.A.) Economics, Bachelor of Arts (B.A.) Economics at Northwestern University
Contributions:2 PRs, 4 pushes, 2 branches in 3 years 3 months
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Marshall Krassenstein - Solutions Architect at Databricks