Director, Head of Data & AI Policy

AstraZeneca UK Limited
Macclesfield, UK
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Artificial Intelligence Cyber Security Information Technology Data Management GXP

Job description

We’re building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you’ll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you’ll have the platform (and sponsorship) to make it real. Introduction to role The Senior Director, Head of Data & AI Policy, Assurance, and Monitoring provides enterprise leadership for the definition, implementation, and assurance of Data and AI standards and controls, including ownership of monitoring, testing, and reporting on control effectiveness. The role ensures that data and AI can be used safely, responsibly, and at scale by translating regulatory, ethical, and risk requirements into pragmatic, automated, and enterprise-wide policies and controls. The role drives policy-to-practice execution by converting standards into embedded controls and overseeing monitoring, assurance, and reporting to senior leadership. Typical Accountabilities Demonstrated leadership of diverse, global teams to achieve the following objectives, consistently exhibiting AZ values: Own, maintain, and right size the enterprise Data & AI standards and control framework, ensuring alignment to business strategy, risk appetite, and external regulations (e.g., AI regulation, data privacy, etc.). Translate regulatory and ethical requirements into clear, pragmatic, and scalable enterprise standards covering use cases for data and AI. Design, build, or partner to successfully embed associated controls for Data & AI into business processes, platforms, and tooling, with a strong focus on automation and “control-by-design”. Drive enterprise-wide adoption of Data & AI standards and controls, operating effectively in a federated environment to influence stakeholders and shape change management plans that enable consistent, sustainable implementation. Drive continuous improvement of standards and controls for Data & AI to reflect stakeholder feedback, emerging technologies, evolving risks, and regulatory change. Serve as the enterprise authority on Data & AI control expectations, providing interpretation and guidance to senior stakeholders, technology teams, and business leaders. Establish monitoring and assurance to evaluate Data and AI control effectiveness and sustain compliance, including reporting to senior leadership through KPIs and maturity measures. Drive improvements in performance measures related to standards and controls. Establish and lead the enterprise operating model for Data & AI Policy, Assurance, and Monitoring, defining clear accountabilities, decision rights, escalation paths, and governance forums, with well-defined stakeholder engagement across business units, regions, and functions.

Requirements

Demonstrated ability to partner effectively with colleagues across functions and levels, actively listen, resolve conflicts constructively, and co-create solutions to achieve shared goals. Demonstrated ability to synthesise complex issues into concise narratives, anticipating stakeholder concerns, navigating ambiguity, and driving alignment and decisions in high-stakes forums. Executive presence with the ability to build credibility quickly, communicate with clarity and confidence, and influence senior executive leadership at forums such as Audit Committee, the Data Enablement Council, or SET-area Data Office (SEDO). Education, Qualifications, Skills, and Experience Essential Bachelor’s degree in business administration, Information/Data Science, Informatics, Computer Science, Economics, or related discipline - or equivalent number of years of experience. In-depth and demonstrated knowledge of standards, controls, assurance, and monitoring for Data and AI capabilities applicable to the Pharma industry. Demonstrated ability to build and lead a high-performing team with deep expertise in enterprise Data & AI standards and controls. Champion a culture of responsible, compliant, and value-focused use of data and AI across the organisation. Familiarity and up to date with relevant data and AI regulations and compliance requirements (e.g. GxP, GDPR, EU AI Act, NIS2, etc.) Proven ability to develop strong partnerships with other areas of the business such as Legal, Compliance, Cyber Security, Enterprise Risk Management, Data Offices, etc.). Demonstrated project leadership skills. Demonstrate effective communication skills with the ability to influence others to achieve objectives. Proven change management, collaboration, and negotiation skills. Desirable Master’s or PhD in Business Administration, Information/Data Science, Informatics, Computer Science, Economics, or related discipline. Experience in life sciences and healthcare. Intimate knowledge of relevant key business processes in the Pharma industry. Technical ability to operationalise controls through automation (“control-by-design”). Practical knowledge of ISO/IEC 42001 (Artificial Intelligence Management Systems). Practical knowledge of NIST AI Risk Management Framework. Data and / or AI Governance and Data Management education and certifications. Applied data management, data science, AI development, or AI governance skills, including experience with related tools. Experience leading teams responsible for red-teaming, control testing, and second-line assurance over Data & AI risks and controls. Exposure publishing relevant data and / or AI governance and policy topics in peer-reviewed journals, conferences, and other scientific proceedings.

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