Interview
summary
Building intelligence insights on activity data like emails and meetings to surface where deals sit in the sales pipeline and help managers make decisions. Uses Scala as a bridge from Java into functional programming and advocates shapeless for compile-time guarantees to avoid throwing away type information. Focuses on merging functional programming techniques with machine learning workflows, citing Cats/Typelevel tools and composition over brittle inheritance as the practical path forward. Activity-data-driven ML for sales
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