Senior Data Scientist

Job description

About seQura seQura provides innovative, flexible and easy-to-use payment technologies that help merchants acquire, convert and retain more customers. We make a difference in sales performance by tailoring our solutions to different sectors, to address their unique pain points and deliver superior results in Retail, Education, Eyewear, Repairs and Travel. We also empower smart shopping to consumers who seek more value, convenience, and flexibility in their shopping, with new payment experiences that allow them to save, access interest-free credit, or pay in small, comfortable installments of up to 24 months. Born in Barcelona, seQura is a privately-owned fintech, currently expanding throughout southern Europe and Latin America, growing above 50% CAGR. Over 6000 businesses, almost 3 million shoppers, and almost 400 employees continue to rate us as one of the most loved and trusted fintechs out there, with an NPS of 87%, a Trustpilot rating of 4.7/5, and a Glassdoor rating of 4.1/5. About the role 🤓 We are looking for a Senior Data Scientist to help design, build, and evolve the intelligence behind seQura's Shopper App — a shopping app where users manage the payments they've made with seQura and discover and shop across merchants with rewards. This role focuses on building production-grade machine learning systems that bring intelligence into real user flows. You will work on smart search, recommendations, and agent capabilities — models that understand context, reason over shopper needs, and help users discover and shop in ways that are relevant, personalized, and safe. You will collaborate closely with Product, Frontend, Data, and AI teams, playing a key role in shaping both the technical approach and the shopper experience. What challenges you'll be solving 🚀 Designing, building, and shipping the recommendation systems that power the Shopper App, helping users discover relevant merchants, products, and offers across the full shopping lifecycle, while writing simple, clean, and efficient code. Improving smart search — relevance, ranking, intent detection, and query understanding — so shoppers quickly find what they're looking for. Turning ambiguous shopper needs and product ideas into reliable, scalable ML systems through a pragmatic, analytical, and accountable approach — favoring simplicity and iteration over premature complexity. Owning the full model…