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I\u2019ve said it before and I\u2019ll say it again: \u201cdata science\u201d is an ambiguous job title. People use the term to refer to data science, data engineering, machine learning engineering and analytics roles, and that\u2019s bad enough. But worse still, being a \u201cdata scientist\u201d means completely different things depending on the scale and stage of the company you\u2019re working at. A data scientist at a small startup might have almost nothing in common with a data scientist at a massive enterprise company, for example.

So today, we decided to talk to someone who\u2019s seen data science at both scales. Jay Feng started his career working in analytics and data science at Jobr, which was acquired by Monster.com (which was itself acquired by an even bigger company). Among many other things, his story sheds light on a question that you might not have thought about before: what happens to data scientists when their company gets acquired?