Data & AI Governance Lead at Bayer AG - USA

Carnaxide, Balearic Islands, Portugal -

Full Time

Start Date

Immediate

Expiry Date

09 Oct, 26

Salary

0.0

Posted On

11 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Governance, AI Governance, Master Data Management, Responsible AI, Risk Management, Stakeholder Management, Regulatory Compliance, Data Quality Frameworks, GenAI, Agentic AI, SAP S/4HANA, Change Management, Data Privacy, Data Lifecycle Management, Strategic Leadership, Executive Communication

Industry

Chemical Manufacturing

Description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Data & AI Governance Lead Data & AI Governance Lead is experience defining governance strategy, data quality frameworks, and responsible AI controls across global commercial environments. Strong track record of translating complex regulatory, privacy, compliance, and technical requirements into practical governance capabilities that improve data trust, audit readiness, AI readiness, and business adoption. Brings a rare combination of strategic leadership and hands-on delivery: establishing 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. Experienced in shaping pragmatic Data & AI governance for Data Governance, AI, Agentic AI, and GenAI use cases with needed management, human oversight, privacy, transparency, and risk management. Skilled at partnering with Legal, Privacy, Compliance, Regulatory, Ethics, product teams, and external data providers to embed governance into systems and ways of working. Known for making governance a business enabler rather than a control function only: driving adoption through stakeholder engagement, education, change management, and clear accountability while helping teams move faster with trusted, high-quality, and compliant data. THIS ROLE IS POSTED IN MULTIPLE LOCATION PLEASE APPLY TO THE LOCATION YOU PREFER Core Experience & Impact Support 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 (e.g., improved data quality, audit readiness, and trusted, compliant data use). Data & AI compliance in contracts & TPAs — embed AI compliance and risk controls into third-party agreements (TPAs), vendor contracts, and internal data and AI engagements — defining AI and acceptable-use clauses, data-lineage and provenance requirements, IP and usage rights, bias and transparency expectations, and assurance/acceptance criteria — so the business stays AI-compliant and free of avoidable risk with both external vendors and internal teams. Partner with domain leads to establish scalable governance frameworks and maintain global data-readiness assessments across critical business domains. External data & vendor standards — establish governance expectations for external data collaborations and vendor data, including standards, transfer criteria, quality acceptance, usage rights, and AI-related controls. Contribute to master data management initiatives for Consumer Health, strengthening consistency, quality, ownership, and reuse of key commercial data assets. AI bias & fairness frameworks and launch readiness — co-develop AI bias and fairness frameworks and clear launch-readiness criteria that define when a GenAI or Agentic use case (e.g. “Talk to Data”) is good enough to go live — setting fairness and accuracy thresholds, evaluation and benchmarking approaches, human-oversight requirements, and go/no-go gates, with continuous monitoring after launch. Define fit-for-purpose governance policies and processes that ensure data is generated with quality and consumed compliantly and confidently across the business. Establish data lifecycle governance controls — covering data creation, approval, change management, versioning, lineage, retention, archiving, and retirement — to ensure data remains traceable, audit-safe, compliant, and fit for trusted business and AI use. Collaborate with adjacent data disciplines (e.g., metadata descriptions, reference and master data, data modeling, cataloging, lineage) to support fitness-for-use, AI readiness, and auditability. Translate data and AI governance frameworks into practical system and workflow requirements, in partnership with Data & AI product teams and IT. Built strong partnerships with enterprise and local Stewards to capture domain insight, resolve adoption barriers, and continuously improve governance implementation. Serve as the interface to Legal, Privacy, Compliance, Regulatory, and Ethics teams to interpret requirements and design pragmatic, fit-for-purpose governance frameworks. Partner with existing data use and global compliance councils to operationalize Responsible AI standards (fairness, transparency, privacy, safety, explainability, human oversight) across the lifecycle. Combine strategic leadership with hands-on contribution when needed (e.g., acting as data steward, process owner, or project manager for governance initiatives). Drive 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. Qualification & Competencies: Master’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. Minimum 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. Senior experience in Consumer Health, Pharma, FMCG, or other regulated commercial environments, with strong understanding of commercial, market, customer, product, and external data domains. Demonstrated leadership capability in cross-functional projects, with experience establishing and embedding MDM governance structures across business, data, and technology teams. Strong knowledge of SAP S/4HANA in a master data context, with familiarity across enterprise systems such as ERP, PIM platforms including, CRM, and related commercial data ecosystems. Practical know-how in data models, system integrations, and Golden Record logic, including the ability to translate business requirements into robust master data structures and integration principles. Proven 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. Strong AI, GenAI, Agentic AI, and analytics fluency, with practical understanding of data readiness, model lifecycle governance, human oversight, transparency, explainability, monitoring, change control, and risk mitigation. Deep knowledge of data privacy, regulatory, compliance, security, and third-party data usage requirements, with the ability to translate legal and risk requirements into practical business and technology controls. Strong stakeholder leadership and influencing skills, able to bridge business, commercial, product, data, technology, legal, privacy, compliance, and ethics communities without relying on formal authority. Strategic and conceptual thinker with the ability to identify cross-functional patterns, simplify complexity, prioritize value, and balance business opportunity with regulatory, ethical, operational, and technology risks. Excellent executive communication, facilitation, and change management capabilities, with the ability to drive adoption, build data literacy, and make governance practical for business and technical audiences. Fluent in English must & other language beneficial YOUR APPLICATION This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health, feeding growing populations and slowing the rate of climate change. You have a voice, ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer. Bayer 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. Location: Spain : Cataluña : Barcelona || Portugal : Estremadura : Carnaxide Division: Consumer Health Reference Code: 876498

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Responsibilities

Lead the data and AI governance strategy and roadmap to ensure compliant, high-quality, and trusted data use across global commercial environments. Establish frameworks for AI bias, fairness, and risk controls while partnering with legal and technical teams to embed governance into business workflows.