Jose Garcia didn't just grow Skyscanner's data organisation from 13 to around 60 people — he made sure impact grew with it, across the data science, marketing and ad tech teams he leads. We unpack the challenges of prioritising the right problems instead of the most interesting ones, building leadership layers that don't bottleneck through him, and why he thinks great data science has never really been about the models.
We also get into how AI tools like Claude are beginning to change the skills, hiring decisions and day-to-day ways of working inside modern data teams.
We cover:
How Skyscanner's data org grew from 13 to 60 without losing focus
Why business impact is harder to prove than most data teams expect
Jose's method for prioritising the right problems, not the interesting ones
What actually changes about leadership once a team crosses a certain size
How AI is reshaping who data teams hire and what they're hired for
A practical conversation about data science, leadership, scaling teams and the impact of AI.
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