Senior Director, Head of Data & AI Risk Management

Posted 5 Days Ago
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London, England, GBR
In-Office
Senior level
Biotech • Pharmaceutical
The Role
Leads enterprise Data and AI risk management across strategic, operational, ethical, and regulatory domains. Establishes governance, operating models, risk appetite alignment, reporting, controls, remediation, and escalation processes. Advises executives on complex AI use cases, embeds risk management into delivery practices, and oversees compliance initiatives involving the EU AI Act, US Data Security Program, and other regulations. Builds global teams and partners with Legal, Compliance, Cyber Security, Privacy, Internal Audit, and business leaders to enable responsible AI deployment.
Summary Generated by Built In

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. 

  • 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. 

  • 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 decisionmaking and informed discussions related to risk appetite. 

  • 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. 

  • Sponsor and / or lead priority initiatives across Data & AI Trust and Assurance, irrespective of team boundaries, including Standards and Controls rollout and regulatory compliance programmes covering requirements such as the US Data Security Program, EU AI Act, European Health Data Space, and other emerging obligations. 

  • 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 highstakes 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 secondline oversight within a complex organisation. 

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

  • Sponsor and / or lead priority initiatives across Data & AI Trust and Assurance, irrespective of team boundaries, including Standards and Controls rollout and regulatory compliance programmes covering requirements such as the US Data Security Program, EU AI Act, European Health Data Space, and other emerging obligations. 

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

  • 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. 

  • 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. 

  • 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. 

Why AstraZeneca?   

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.   

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. 

#EAI 

Date Posted

17-sept-2026

Closing Date

06-oct-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

Skills Required

  • Bachelor's degree in Business Administration, Information or Data Science, Informatics, Computer Science, Economics, or a related discipline, or equivalent experience.
  • Significant senior experience in risk management, assurance, governance, or second-line oversight within a complex organization.
  • Experience building and leading high-performing teams with enterprise Data and AI risk management expertise.
  • Experience sponsoring or leading Data and AI Trust and Assurance initiatives, standards and controls rollouts, and regulatory compliance programs.
  • Ability to champion responsible, compliant, and value-focused use of data and AI.
  • Ability to build partnerships with Legal, Compliance, Cyber Security, Enterprise Risk Management, and Data Offices.
  • Demonstrated project leadership skills.
  • Effective communication and influencing skills.
  • Proven change management, collaboration, and negotiation skills.
  • Master's or PhD in Business Administration, Information or Data Science, Informatics, Computer Science, Economics, or a related discipline.
  • Experience in life sciences and healthcare.
  • Knowledge of relevant business processes in the pharmaceutical industry.
  • Practical knowledge of ISO/IEC 42001.
  • Practical knowledge of the NIST AI Risk Management Framework.
  • Data or AI Governance and Data Management education or certifications.
  • Familiarity with GxP, GDPR, EU AI Act, NIS2, and related data and AI regulations.
  • Applied data management, data science, AI development, or AI governance skills, including experience with related tools.
  • Experience publishing relevant data or AI risk management topics in peer-reviewed journals, conferences, or scientific proceedings.

AstraZeneca Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.

  • Fair & Transparent Compensation Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
  • Strong & Reliable Incentives Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
  • Retirement Support A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.

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The Company
HQ: Gaithersburg, MD
70,000 Employees
Year Founded: 1999

What We Do

We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.

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