Paul Larsen

Data scientist, PhD in mathematics and Rhodes Scholar with over 10 years of experience in both enterprise and startups. My hobbies are masters swimming, reading and walking our dogs.

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Head of Data + AI

My professional motto is “In theory, there’s no difference between theory and practice. In practice, there is” (Yogi Berra). What I love about data science in a business context is that the field is still young and volatile enough that you need a good amount of (interesting) theory, while the real business needs keep you grounded in what’s truly useful. “Interesting” is not enough–data science must generate value for the customer in practice.

My work experience has been mainly in financial services, starting at Deutsche Bank before switching to insurance with Allianz SE. Most recently I led data science teams in FinTech and InsureTech startups.

Currently I help companies succeed with nearly all things data and AI, from scoping through to production, using whatever AI best suits their needs. All the while respecting the volatility of AI’s principal dependency: data.

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Key expertise



Data quality

Expert cases