Sr. Scientist / APS, Data Compliance & Governance Management

Introduction to role
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?
About the Beijing AI Center
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.
Accountabilities:
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