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Staff Fullstack Data Analyst (Commercial Analytics)

Pleo · London

Publicada em 25/09/2026

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About PleoMessy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. At Pleo, we're changing that. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike - with a vision to help all businesses ‘go beyond’.The word ‘Pleo’ actually means ‘more than you’d expect’, and living by that mantra has been the secret to our success over the last 10 years.Now, we’re at a pivotal moment in our journey; every move we make has a direct impact on our 40,000+ customers, our business, and our collective success. We need people who take pride in uncovering customer needs, who turn complex problems into simple solutions, challenge the way things are done (respectfully), and always aim high. With great ambitions driving us forward, we can’t say we’ve got this whole thing figured out. And frankly, that’s half the fun! What we can say is that we’re a driven, progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together.Please note: Applications will be open until 3rd October 2026 at 10.00 CEST. We will not review any application before the closing window so, please, don't rush to apply and ensure you use the time to submit a high quality, personalised application. About the roleGrowth Intelligence owns the commercial data layer that powers Pleo's GTM engine — acquisition, retention, propensity modelling, and customer health. The team supports RevOps, Customer Experience, Customer Success, and senior commercial leadership with the data and models they need to make faster, smarter decisions.As a Staff Full Stack Data Analyst, you are the senior technical voice for commercial analytics at Pleo. You set the architectural direction for Growth Intelligence's analytics layer, define what good looks like for the team, and shape how GTM data is structured,
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