Data & AI Governance Lead
6 days ago
Barcelona
p h3Data AI Governance Lead /h3 pLead Data AI Governance across Bayer Consumer Health, defining strategy, data quality frameworks, and responsible AI controls across global commercial environments. Translate regulatory, privacy, compliance, and technical requirements into practical governance capabilities that improve data trust, audit readiness, AI readiness, and business adoption. /p pPlay a dual role of strategic leadership and hands‑on delivery: establish decision rights, stewardship and custodian models, policies, standards, data quality processes, master data management practices, and governance workflows that enable compliant, confident, and scalable data use across business, analytics, product, and IT teams. /p h3Core Experience Impact /h3 ul liSupport and deliver the data and AI governance strategy and multi‑year roadmap, aligned with Consumer Health priorities and Data AI ambitions, to yield measurable outcomes such as improved data quality, audit readiness, and trusted, compliant data use. /li liEmbed AI compliance and risk controls into third‑party agreements, vendor contracts, and internal engagements—defining AI and acceptable‑use clauses, data‑lineage and provenance requirements, IP and usage rights, bias and transparency expectations, and assurance/acceptance criteria. /li liPartner with domain leads to establish scalable governance frameworks and maintain global data‑readiness assessments across critical business domains. /li liEstablish governance expectations for external data collaborations and vendor data, including standards, transfer criteria, quality acceptance, usage rights, and AI‑related controls. /li liContribute to master data management initiatives for Consumer Health, strengthening consistency, quality, ownership, and reuse of key commercial data assets. /li liCo‑develop AI bias and fairness frameworks and clear launch‑readiness criteria that define when a GenAI or Agentic use case is good enough to go live—setting thresholds, evaluation and benchmarking approaches, human‑oversight requirements, and go/no‑go gates, with continuous monitoring after launch. /li liDefine fit‑for‑purpose governance policies and processes that ensure data is generated with quality and consumed compliantly across the business. /li liEstablish data lifecycle governance controls covering creation, approval, change management, versioning, lineage, retention, archiving, and retirement to keep data traceable, audit‑safe, and compliant. /li liCollaborate with adjacent data disciplines (metadata, reference data, data modeling, cataloging, lineage) to support fitness‑for‑use, AI readiness, and auditability. /li liTranslate governance frameworks into practical system and workflow requirements in partnership with Data AI product teams and IT. /li liBuild strong partnerships with enterprise and local stewards to capture domain insight, resolve adoption barriers, and continuously improve governance implementation. /li liServe as the interface to Legal, Privacy, Compliance, Regulatory, and Ethics teams to interpret requirements and design pragmatic, fit‑for‑purpose governance frameworks. /li liPartner with existing data use and global compliance councils to operationalize Responsible AI standards across the lifecycle. /li liCombine strategic leadership with hands‑on contribution when needed—acting as data steward, process owner, or project manager for governance initiatives. /li liDrive adoption through change management, communications, and education, making governance practical for business, marketing, sales, and analytics teams while building accountability, data literacy, and risk‑aware innovation. /li /ul h3Qualifications Competencies /h3 ul liMaster’s degree in business, economics, data science, information management, computer science, or a related field; advanced degree or relevant certifications in data governance, privacy, risk, compliance, or AI governance are an advantage. /li liMinimum 10 years of solid professional experience in master data management, data governance, or data‑driven transformation programs, ideally within global, matrixed, or regulated business environments. /li liSenior experience in Consumer Health, pharma, FMCG, or other regulated commercial environments, with strong understanding of commercial, market, customer, product, and external data domains. /li liDemonstrated leadership capability in cross‑functional projects, establishing and embedding MDM governance structures across data, business, and technology teams. /li liStrong knowledge of SAP S/4HANA in a master data context and familiarity with ERP, PIM, CRM, and related commercial data ecosystems. /li liPractical know‑how in data models, system integrations, and Golden Record logic, translating business requirements into robust master data structures and integration principles. /li liProven ability to design, operationalize, and scale enterprise data governance frameworks, including data ownership, stewardship, data quality, metadata, lineage, master/reference data, cataloging, controls, and KPI‑based governance performance management. /li liStrong AI, GenAI, Agentic AI, and analytics fluency, understanding data readiness, model lifecycle governance, human oversight, transparency, explainability, monitoring, change control, and risk mitigation. /li liDeep knowledge of data privacy, regulatory, compliance, security, and third‑party data usage requirements, translating legal and risk requirements into practical business and technology controls. /li liStrong stakeholder leadership and influencing skills, bridging business, commercial, product, data, technology, legal, privacy, compliance, and ethics communities without formal authority. /li liStrategic and conceptual thinker, simplifying complexity, prioritizing value, and balancing business opportunity with regulatory, ethical, operational, and technology risks. /li liExcellent executive communication, facilitation, and change management capabilities, driving adoption, building data literacy, and making governance practical for both business and technical audiences. /li liFluent in English; other languages are beneficial. /li /ul h3Location /h3 pSpain: Catalonia: Barcelona | Portugal: Estremadura: Carnaxide /p h3Division /h3 pConsumer Health /p h3Reference Code /h3 h3Bayer welcomes applications from all individuals /h3 pBayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination. /p /p #J-18808-Ljbffr