Senior Director, Data & AI Risk Management

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. 

The Senior Director, Data & AI Risk Management provides enterprise leadership for the identification, assessment, and management of Data and AI risks. The role ensures that Data and AI are deployed at scale while remaining within agreed risk appetite, regulatory expectations, and ethical standards. This role acts as a senior risk authority and trusted partner to the business, translating policy intent into practical risk decisions, driving mitigation where needed, and enabling leaders to make confident, timely decisions on Data & AI initiatives. 

Typical Accountabilities:  

• Demonstrated leadership of diverse, global teams to achieve the following objectives, consistently exhibiting AZ values: 

• Own the enterprise approach to identifying, assessing, and managing Data & AI risks across strategic, operational, ethical, and regulatory dimensions. o Integrate Data & AI risk into broader Enterprise Risk Management (ERM) processes, ensuring alignment with enterprise risk appetite and strategic objectives.  

• Ensure material Data & AI risks are surfaced, understood, and actively managed at an enterprise level. o Improve enterprise risk posture by challenging the adequacy of mitigations, driving timely remediation of material issues, and escalating where risks exceed agreed appetite or controls are ineffective.  

• Provide harmonised risk positions that support confident, timely decision-making and informed discussions related to risk appetite. o Oversee enterprise-level risk aggregation, reporting, and insight for Data & AI, providing senior leadership and governance bodies with a clear view of systemic risk exposure, trends, and residual risk against appetite.  

• Establish and lead the enterprise operating model for Data & AI Risk Management, defining clear accountabilities, decision rights, escalation paths, and governance forums, with well-defined stakeholder engagement across business units, regions, and functions.  

• Drive continuous improvement of risk management processes for Data & AI to reflect stakeholder feedback and industry best practices.  

•  Serve as a senior advisor on complex or novel Data & AI use cases, enabling proportionate risk decisions rather than default risk avoidance.  

• Partner with Business areas, Project Teams, and Data Offices to embed risk management into ways of working, delivery pipelines, and operating models.  

• Build strong relationships across Legal, Compliance, AZ IT, and Privacy to ensure aligned and consistent risk approaches.  

• Own and manage interactions with Group Internal Audit, including Management Action Plans, and remediation tracking related to Data & AI risk.  

• Identify opportunities to safely accelerate Data Enablement and AI deployment within agreed risk appetite.  

• 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), promoting a culture of responsible and confident Data & AI use. 

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.  

• Significant senior experience in risk management, assurance, governance, or second-line oversight within a complex organisation.  

• Demonstrated ability to build and lead a high-performing team with deep expertise in enterprise Data & AI risk management.  

• Champion a culture of responsible, compliant, and value-focused use of data and AI across the organisation.  

• 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.  

• Data and / or AI Governance and Data Management education and certifications. Familiarity with relevant data and AI regulations and compliance requirements (e.g. GxP, GDPR, EU AI Act, NIS2, etc.).  

• Applied data management, data science, AI development, or AI governance skills, including experience with related tools.  

• Exposure publishing relevant data and / or AI risk management topics in peer-reviewed journals, conferences, and other scientific proceedings. 

Office Working Requirements 

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. 

The annual base pay (or hourly rate of compensation) for this position ranges from $ 176.677,60  - $ 265.016,40 USD Annual, either as annual base pay or as the hourly rate (annual base pay divided by 2080 hours)]. Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.    

AstraZeneca offers the chance to shape a truly digital and data-led enterprise where work directly influences how life-changing medicines are discovered, developed, and delivered. Here technology platforms, advanced analytics, AI and machine learning are combined with leading science to solve complex problems at pace. Colleagues are encouraged to experiment with modern tools, challenge the status quo, learn continuously through initiatives such as hackathons and mentoring programmes, and collaborate across diverse teams and functions. With strong investment in data capabilities and a constant flow of new challenges in emerging areas, this is a place to take ownership, grow quickly, build industry-defining solutions and see the impact of your work on patients worldwide. .  

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