Director, Data & AI Risk Management

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title as heading. Must not include Job ID etc. Must remove boilerplate, navigation, legal, EEO, scam warning, duplicated lines, application instructions. Must preserve all substantive info. We need to parse the posting. First paragraph: "We're building a connected, end-to-end Enterprise AI engine ..." This is about the role? It's describing the environment. Could be "About the role" or maybe "About the team". We'll put under About the role. Then: "Success depends on being exceptional connectors..." also about role. Then: "The Director, Data & AI Risk Management, leads and delivers enterprise risk management activities..." This is role description. Could be part of About the role. Then "Typical Accountabilities" list: bullet points. Those are responsibilities. Then "Essential Education, Qualifications, Skills, and Experience" includes bullet-like paragraphs. We need to separate into sections: Qualifications, Skills, Experience? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content. We have: - About the role: intro paragraphs. - Responsibilities: the "Typical Accountabilities" list. - Requirements: maybe "Essential Education, Qualifications, Skills, and Experience" includes education, qualifications, skills, experience. But we have separate headings for Qualifications and Skills. Could split: Qualifications (education, experience), Skills (specific skills). But we need to preserve all info. We also have "Desirable" section: Master's degree, industry experience, etc. Could be part of Qualifications (preferred) or maybe separate but we can include under Qualifications as desirable. We have Benefits: "Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans." Pay: "The annual base pay (or hourly rate of compensation) for this position ranges from $153,480.80 - $230,221.20 USD . Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles." Schedule: "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." Thus we have Benefits, Pay, Schedule sections. We must not include boilerplate like "Why AstraZeneca?" maybe that's part of Benefits? Actually "Why AstraZeneca?" includes culture description. Could be part of About the role? But it's more about company. Might be considered fluff but it's substantive about culture. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "Why AstraZeneca?" section is not boilerplate; it's about company culture. Could be included under About the role or maybe a separate section like "About the company". But only allowed headings are the listed ones. We could incorporate into About the role. Also the EEO statement at end: "Our mission is to build an inclusive environment..." that's EEO boilerplate; must remove. Also "#EAI Date Posted 25-Sept-2026 Closing Date 02-Oct-2026" is metadata; drop. Now produce HTML. Structure:

About the role

... paragraphs ...

Responsibilities

• ...
...

Qualifications

... education, experience ...

Maybe also include Desirable as part of Qualifications.

Skills

... skills ...

Benefits

• qualified retirement programs
• paid time off (vacation, holiday, leaves)
• health, dental, and vision coverage

Pay

The annual base pay (or hourly rate of compensation) for this position ranges from $153,480.80 - $230,221.20 USD. Positions offer eligibility for various incentives—short‑term incentive bonuses, equity‑based awards for salaried roles and commissions for sales roles.

Schedule

In‑person work is expected a minimum of three days per week on average, with flexibility to balance office presence and individual needs.

We need to ensure we preserve all substantive info from the posting. Let's extract About the role content: First paragraph: "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." Second paragraph: "The Director, Data & AI Risk Management, leads and delivers enterprise risk management activities that help AstraZeneca identify, assess, govern, report, and reduce Data & AI risk. The role provides practical risk advisory, consulting, governance, and risk appetite support across regulatory compliance, data protection, AI governance, and related risk domains. Reporting to the Senior Director, Data & AI Risk Management, the Director partners across Data & AI Trust and Assurance and with business and enabling functions to translate complex risk and regulatory expectations into clear decisions, proportionate mitigations, and measurable improvements in risk posture. The role also leads cross-functional projects and supports enterprise governance forums and Enterprise Risk Management reporting, enabling responsible and confident use of Data & AI at scale." Third paragraph maybe "Why AstraZeneca?" but we can incorporate. We could also add the "Why AstraZeneca?" description: "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." But note schedule part is duplicated; we already have schedule section. The "Why AstraZeneca?" includes schedule description; we should not duplicate. We'll keep schedule separate and maybe not include that part in About the role. Thus About the role will include first two paragraphs plus maybe the first part of Why AstraZeneca up to before schedule. Let's extract the Why AstraZeneca part before schedule: "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." We can include that as part of About the role. Now Responsibilities: list from "Typical Accountabilities". Let's capture each bullet: - Provide trusted risk advisory, consulting, and risk appetite support across Data & AI risks, helping stakeholders make timely, proportionate, and well-informed decisions. - Provide governance and business analysis support across regulatory compliance, data protection, AI governance, and other Data & AI risk areas, translating complex requirements into clear risk positions, decisions, and actions. - Lead and/or project manage 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. - Improve visibility of Data & AI risk posture by developing clear narratives, indicators, dashboards, and insights on material exposures, trends, mitigations, residual risk, and progress against appetite. - Engage business and functional stakeholders to build relationships and understand risk exposure, challenge the adequacy of mitigations, agree pragmatic remediation, and help drive residual risk and overall risk posture down. - Lead selected aspects of Data & AI risk aggregation, analysis, and reporting for Enterprise Risk Management, senior leadership, and governance bodies. - Facilitate risk assessments, workshops, and decision forums for complex or novel Data & AI use cases, balancing enablement, compliance, and protection of patients, the company, and its information and intellectual property. - Synthesize complex issues into concise, executive-ready narratives; anticipate stakeholder concerns; navigate ambiguity; and influence decisions in high-stakes forums. - Partner with Regulatory Intelligence, Legal, Compliance, Privacy, Cyber Risk, Enterprise Risk Management, Data Offices, and risk teams in R&D, Operations, Commercial, Enabling Units, and other business functions to align risk approaches and accountabilities. - Work across Data & AI Trust and Assurance teams to accomplish shared goals, resolve cross-cutting issues, and deliver integrated outcomes across policy, standards and controls, assurance, monitoring, risk, and regulatory readiness. - Identify opportunities to simplify and continuously improve Data & AI risk management processes, governance, reporting, and stakeholder experience while preserving effective oversight. - Promote a culture of responsible, compliant, and value-focused use of Data & AI, demonstrating AstraZeneca values in all interactions. Now Qualifications: from "Essential Education, Qualifications, Skills, and Experience". Let's parse: - Bachelor's degree in business administration, Risk Management, Information/Data Science, Informatics, Computer Science, Economics, Law, or a related discipline, or equivalent relevant experience. - Significant experience in risk management, assurance, governance, regulatory compliance, or second-line oversight within a complex, global organisation. - Demonstrated experience assessing and managing data, technology, digital, and/or AI risks and translating complex issues into pragmatic business decisions. - Strong project leadership and project management capability, including delivery through cross-functional and matrixed teams, such as Regulatory Compliance, areas of organisational risk, AI governance, or related disciplines. - Experience providing risk advisory or consulting support, including risk appetite, mitigation, escalation, and risk acceptance discussions. - Working knowledge of relevant Data & AI regulatory and compliance requirements, such as the US Data Security Program, EU AI Act, European Health Data Space, GDPR, GxP, NIS2, or comparable frameworks. - Experience with governance forums, executive reporting, risk indicators, dashboards, or Enterprise Risk Management processes. - Strong business analysis, facilitation, and problem-solving skills, with the ability to structure ambiguity and establish clear ownership and actions. This includes working across domains such as regulatory compliance, data protection, AI governance, or related disciplines to translate requirements into clear risk positions, decisions, accountabilities, and actions. - Demonstrated experience developing risk reporting to support senior management decision-making. - Proven ability to build partnerships across Legal, Compliance, Privacy, Cyber Security, Enterprise Risk Management, Data Offices, technology, and business functions. - Excellent written and