Eoin O'Mahony—data science partner at Lightspeed, former Uber science lead, and one of the early architects of the system that kept NYC’s Citi Bikes available across the city—argues that positive metrics are meaningless if you don’t understand the mechanism behind them. At Uber, he was careful to make sure his launches both looked good on paper and made sense in practice. Now in venture, he’s applying that same rigor to unstructured data—using GenAI to scale a kind of work that’s long resisted systematization.
LINKS
Eoin's page at Lightspeed Ventures (https://lsvp.com/team-member/eoin-omahony/)
Ramesh Johari on How to Build an Experimentation Machine and Where Most Go Wrong (https://high-signal.delphina.ai/episode/ramesh-johari-on-how-to-build-an-experimentation-machine-and-where-most-go-wrong)
Chiara Farronato on Data Science Meets Management: Teamwork, Experimentation, and Decision-Making (https://high-signal.delphina.ai/episode/data-science-meets-management)
Delphina's Newsletter (https://delphinaai.substack.com/)

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