Joe Marlo

Joe Marlo is Director of Data Science at Lander Analytics, where he designs agentic workflows, statistical models, and interactive frontends that put rigorous analysis into production. He's authored multiple R packages on sequence analysis and causal inference diagnostics. Previously, he was a quantitative strategist at J.P. Morgan and a data scientist at Verizon. The former role leveraged proprietary big data to understand the spending and saving patterns of Americans and the latter role hierarchical forecasting problems. He holds a master's in applied statistics from New York University and a bachelor's in finance from University of Missouri. Joe is also an assistant research scientist at New York University where he works on thinkCausal, a project to make machine learning methods for causal inference more accessible.

Substack: substack.com/@joemarlo