Level

AstraZeneca

Director/Senior Director, Data Governance (China)

AI in this role

Lead data and AI governance for AstraZeneca's China R&D office, managing regulatory compliance, risk, and cross-border data transfers.

ai-safetydata-governanceregulatory-compliancerisk-managementai-governancedata-privacy

Role Summary

Lead data governance for AstraZeneca’s China R&D office, aligning local policies and controls to enterprise standards. Set policy, assess and mitigate data/AI risk, advise projects, and ensure compliance with China and international regulations, including cross-border data transfer constraints (e.g., Personal Information Protection Law, Cybersecurity Law, and US Department of Justice guidance on bulk transfers). Report functionally to China R&D and dotted line to the Enterprise Data Enablement team and partner with local Chinese teams, Global Compliance, Privacy, Cybersecurity, Quality, Internal Audit and IT Data & Analytics.

Key Responsibilities

  • Strategy and Policy: Localize and implement enterprise Data & AI Policy and standards across China R&D; drive interoperability, reuse, and analytics readiness.
  • Regulatory and Risk: Interpret and operationalize China and global requirements (Personal Information Protection Law, Cybersecurity Law, Data Security Law, Cybersecurity Administration of China). Maintain a data/AI risk register, lead mitigations with Privacy, Legal, and Cyber.
  • Cross-Border and Localization: Govern residency, lawful transfer (Standard Contractual Clauses of China, Cyberspace Administration of China filings, Data Transfer Impact Assessment/Privacy Impact Assessment), de-identification/pseudonymization, and secure access patterns.
  • R&D Enablement: Establish stewardship, metadata, lineage, and data quality rules for clinical, real-world, omics, and imaging data; support FAIR practices.
  • AI Governance: Ensure responsible AI in R&D (model documentation, provenance, validation, monitoring, human oversight).
  • Assurance: Prepare for audits/inspections; design and test privacy/security controls and GxP-aligned data processes.
  • Global Collaboration and Stakeholder engagement: Represent China in EDE forums; feed China requirements into enterprise technology and standards.

Typical Accountabilities

  • Operate the China R&D data governance model, RACI, and councils.
  • Approve classifications, sharing agreements, and data transfer impact assessments.
  • Set KPIs for quality, reuse, access time, and CBDT approvals, lead incident response.

Required Qualifications and Experience

  • Bachelor’s degree, advanced degree preferred.
  • Significant data governance leadership in regulated, multinational biopharma R&D.
  • Deep knowledge of China regulations (PIPL, CSL, DSL, CAC) and global constraints (including US DOJ positions on bulk transfers).
  • Experience with catalogs/lineage, MDM/RDM, data quality, consent/privacy tech, secure research environments, and role-based access control.
  • Strong stakeholder communication; fluent in English and Mandarin.

Desirable Experience

  • Pharmaceutical or biotechnology R&D background, including clinical data standards (e.g., Clinical Data Interchange Standards Consortium), omics/imaging data ecosystems, and real-world data partnerships in China.
  • An understanding of how AI can be used locally to automate and improve data governance processes.
  • Knowledge of enterprise platforms and architectures (e.g., data mesh/data Lakehouse, SAP/MDM, Veeva, Reltio), and privacy-enhancing technologies (tokenization, differential privacy, synthetic data).
  • Experience with global shared services and federated data operating models.
  • Project and change management credentials; Lean/Six Sigma exposure; Power BI/Excel analytics capability.

Date Posted

30-9月-2026

Closing Date

29-11月-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

How we rate this

Director/Senior Director, Data Governance (China) at AstraZeneca rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI SafetyData GovernanceRegulatory ComplianceRisk ManagementAI GovernanceData Privacy

Questions you could be asked

  1. How do you think about the risk of an AI system in this kind of role failing silently?
  2. Tell me about a project where data governance was part of your work. What did you do?
  3. Tell me about a project where regulatory compliance was part of your work. What did you do?
  4. Tell me about a project where risk management was part of your work. What did you do?
  5. Tell me about a project where ai governance was part of your work. What did you do?

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  • List these exact terms on your resume: AI Safety, Data Governance, Regulatory Compliance, Risk Management, and AI Governance. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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