Knowledge Base Scientist Senior - Cdaio

OverviewAs a Senior AI Scientist within Santander’s DAISci, you lead local AI knowledge base projects, translating global standards into scalable, reliable knowledge representations and graph-based data for AI agents.You’ll collaborate with data, engineering, and product teams to connect structured and unstructured data, shaping schemas and retrieval pipelines for conversational systems.Your work enables global AI initiatives to operate at scale while respecting local constraints.This role offers hands-on scientific leadership with impact across markets and platforms.Compensaciones / Beneficioshybrid work modellearning platforms and SantanderOpen Academycompetitive salary with performance-based bonusesBeHealthy wellness programchildcare supportSantander Contigo advisory servicesResponsabilidadesDesign, develop, and maintain local Knowledge Base instances with connected structured/unstructured dataShape graph schemas, entity resolution, metadata, and retrieval pipelines to support AI agents and conversational systemsEnsure alignment with global standards while adapting to local regulatory, linguistic, and business constraintsCollaborate with data engineering and product teams to translate architecture into practical local solutionsContribute to evaluation frameworks, monitoring, and continuous improvement of Knowledge Base componentsShare learnings with global Knowledge Base leadership and propagate reusable patterns across marketsRequisitos principales5-10 years of experience in AI, data science, or ML systems in productionExperience designing and operating scalable, reliable data pipelines or AI systemsExperience collaborating across engineering, product, and business teams to deploy AI-enabled systemsAbility to translate architectural guidance into practical local solutionsStrong individual contributor with ownership in a distributed, multi-country AI organizationExpertise in knowledge representation, graph modeling, semantic data structures, or information retrievalPractical background in ML and modern AI architectures related to structured knowledge and retrievalStrong Python programming skills and familiarity with data processing and graph technologiescollaboration across cross-functional teamsscientific rigor and methodical approachownership and responsibility as an individual contributorknowledge representationgraph modelingsemantic data structures

Share learnings with global Knowledge Base leadership and propagate reusable patterns across markets Requisitos principales5-10 years of experience in AI, data science, or ML systems in production Experience designing and operating scalable, reliable data pipelines or AI systems Experience collaborating across engineering, product, and business teams to deploy AI-enabled systems Ability to translate architectural guidance into practical local solutions Strong individual contributor with ownership in a distributed, multi-country AI organization Expertise in knowledge representation, graph modeling, semantic data structures, or information retrieval Practical background in ML and modern AI architectures related to structured knowledge and retrieval Strong Python programming skills and familiarity with data processing and graph technologies collaboration across cross-functional teams scientific rigor and methodical approach ownership and responsibility as an individual contributor knowledge representation graph modeling semantic data structures