Sr. Scientist / APS, Data Compliance & Governance Management Full-time NEW

Cross-Border Scientific Data Transfer Readiness Owner

Are you ready to turn complex cross-border data rules into practical pathways that unlock AI-driven drug discovery? Do you thrive at the intersection of scientific data, regulatory interpretation, and operational execution where your decisions enable researchers to move faster with confidence?

The Beijing AI Center is a new strategic investment by AstraZeneca to accelerate drug discovery through AI. The center brings together AI researchers, computational scientists, and platform engineers to apply foundation models, agentic AI, and large-scale scientific computing to real R&D problems. Situated in one of the world's most dynamic AI talent markets, it operates at the intersection of biologics discovery, computational chemistry, and AI-driven drug discovery.

The center is structured around three pillars: Discovery verticals (therapeutic design and preclinical predictions), Data & AI Platforms, and Ecosystem Partnerships with leading Chinese academic institutions and AI companies.

This role is the transfer-readiness owner for enabling cross-border scientific data access into China for the Beijing AI Center. It addresses the operational gap that exists before formal approval: the preparation work needed to ensure incoming data requests are assessed against sending-jurisdiction restrictions, appropriately scoped, decision-ready, and auditable.

The primary data flow is global AstraZeneca R&D into China. The Beijing AI Center needs access to molecular libraries, assay data, omics reference sets, compound data, clinical datasets, and other scientific assets from AstraZeneca's global portfolio to power AI-driven drug discovery. The regulatory challenge sits largely on the sending side — determining what can be transferred or accessed given restrictions (e.g., DOJ EO 14117) on bulk sensitive personal data, export control considerations, and AstraZeneca's internal data governance policies — as well as ensuring appropriate classification and protection once data arrives in China.

This is not a final approver role. Rather, it is a dedicated role focused on first-pass triage, provenance tracing, metadata review, annotation coordination, evidence package preparation, and process tracking. The role is intended to reduce the fragmented burden currently carried in an ad hoc way by scientists, business teams, and SMEs, especially for China-related or otherwise non-standard requests.

The immediate priority is China data transfer, but the role should be designed for broader global cross-border sharing. The role will help stabilize the current interim process while building a more scalable and consistent operating model that can inform a future integrated solution.

This role sits at the intersection of scientific data, compliance preparation, and operational execution. It requires enough breadth across R&D data domains and cross border transfer regulations to work effectively across biologics, small molecules, and safety-related contexts, while also knowing when to pull in domain SMEs, the R&D Data Office, Privacy, Compliance, and designated approvers.

What You Will Do

Transfer Readiness & First-Pass Triage

• Design and own the intake process for cross-border data sharing requests — including request workflow, queue management, prioritization criteria, and routing logic
• Own first-pass intake triage for cross-border data sharing requests, with mandatory review for China-related or non-standard requests and simplified routing for straightforward requests
• Check request completeness including business justification, recipient, intended use, data source, format, and baseline supporting information
• Provide first-pass triage recommendation on whether a request is likely in scope, out of scope, or ambiguous, while preparing the supporting rationale for formal review
• Escalate ambiguous or higher-risk cases to the R&D Data Office, SMEs, and designated approvers with clear questions and structured evidence
• Manage DOJ compliance assessment for CRO ordering — evaluating data shared with China-based CROs against EO 14117 thresholds and transaction type classifications

Provenance Tracing, Annotation & Metadata Coordination

• Lead provenance tracing for legacy or incompletely documented datasets by reviewing records, systems, and source history across relevant platforms
• Coordinate metadata collection and completion needed to support transfer assessment and downstream usability
• Support annotation and evidence preparation so datasets are sufficiently described, contextualized, and auditable before review
• Partner with bioinformatics and scientific SMEs to resolve data history, source, ownership context, and metadata gaps
• Differentiate between new / well-annotated data and legacy / incomplete data, applying a lighter path for the former and a deeper tracing effort for the latter

Data Curation & China-Readiness

• Curate and annotate scientific data assets (e.g., structure data in GDB) to ensure datasets are complete, well-structured, and usable for Beijing AI Center workstreams
• Perform structure data curation supporting both Biologics Engineering and Small Molecules domains
• Apply appropriate ontologies, standardized formats, and metadata tagging to support cross-domain reuse and AI/ML consumption
• Partner with domain scientists to resolve data quality, completeness, and annotation gaps prior to transfer

Workflow Management & Process Improvement

• Prepare structured evidence packages for Data Owners, Data Stewards, and designated approvers so requests are decision-ready before formal review
• Track the interim data sharing process from intake through approval, transfer execution, validation, and closure
• Act as process coordinator / tracker during transfer execution, following up on dependencies and ensuring documentation is complete, without taking over technical execution tasks
• Capture recurring issues, requirements, and control points from the interim process to support the design of a future integrated data sharing solution
• Improve templates, checklists, trackers, SOP inputs, and audit-readiness practices over time

Cross-Functional Partnership & Training

• Work with the R&D Data Office to identify what data is likely in scope or out of scope across different workstreams
• Partner with Privacy and Compliance to ensure transfer assessments reflect current privacy requirements and that escalation pathways are well-defined
• Build practical understanding of the systems used across biologics, small molecules, and safety and how data is stored, annotated, accessed, and extracted from separate systems
• Provide guidance to business and scientific teams on transfer readiness expectations, required metadata, and supporting information
• Reduce ad hoc burden on scientists and business teams by becoming the clear owner of the manual preparation work needed before approval

Essential Skills/Experience:

• Education: BSc/ MSc, or equivalent advanced training in life sciences, bioinformatics, data science, information management, or a related field preferred
• Years: Significant experience in pharmaceutical or biotech R&D data environments, typically 4+ years post-qualification
• Domain breadth: Experience spanning multiple stages of drug discovery and development and/or multiple scientific data domains (e.g., discovery, preclinical, clinical, post-market)
• Core expertise: Practical experience in one or more of: scientific data management, data stewardship, data governance, research data operations, data privacy operations, or regulated data workflows
• Cross-border data work: Experience assessing, preparing, or supporting cross-border data sharing decisions — particularly understanding sending-side regulatory requirements and how to structure compliant access
• Governance preparation: Experience preparing information for governance, compliance, or approval decisions — not only executing downstream data processing

Skills

• Regulatory literacy: Ability to understand and operationalize requirements from multiple regulatory frameworks (US DOJ, internal policy) at a working level — sufficient to perform first-pass assessment and know when to escalate to Legal
• DOJ EO 14117 familiarity: Working understanding of the DOJ's bulk sensitive personal data framework — including threshold categories, covered transaction types, prohibited vs. restricted classifications, and exemption pathways — is strongly preferred
• Domain-specific data skills: Familiarity with structural biology/chemistry data, molecular data formats, and scientific annotation standards (e.g., structure-activity relationships, compound descriptors, GDB or equivalent platforms)
• Domain versatility: Ability to work across biologics, small molecules, clinical, omics, imaging, and safety-related data contexts with enough breadth to assess data content and origin
• Analytical rigor: Ability to assess data volumes against thresholds, map data to jurisdictions, evaluate exemption applicability, and structure clear decision-support documentation
• Operational discipline: Strong documentation rigor, process discipline, and audit mindset
• Stakeholder management: Credibility across scientists, AI researchers, SMEs, legal/privacy teams, and governance approvers —