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 worlds most dynamic AI talent markets itoperatesat the intersection ofbiologicsdiscovery 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:thepreparationwork 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 AstraZenecas global portfolio to power AI-driven drug discovery. The regulatory challenge sits largely on the sending side determining what can be transferred or accessed givenrestrictions(e.g.DOJEO14117)on bulk sensitive personal data export control considerations and AstraZenecas 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.Therole will help stabilize the current interim process while building a more scalable and consistent operating model that caninforma 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 domainsand cross border transfer regulationsto work effectively across biologics small molecules and safety-related contexts while also knowing when to pull in domain SMEs the R&D Data OfficePrivacy Complianceand designated approvers.

What You Will Do

Transfer Readiness & First-Pass Triage

• Design and own the intake processfor cross-border data sharing requests including request workflow queue management prioritization criteria and routing logic

• Own first-pass intake triagefor cross-border data sharing requests with mandatory review for China-related or non-standard requests and simplified routing for straightforward requests

• Check request completenessincluding business justification recipient intended use data source format and baseline supporting information

• Provide first-pass triage recommendationon 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 casesto 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 tracingfor legacy or incompletely documented datasets by reviewing records systems and source history across relevant platforms

• Coordinate metadata collection and completionneeded to support transfer assessment and downstream usability

• Support annotation and evidence preparationso datasets are sufficiently described contextualized and auditable before review

• Partner with bioinformatics and scientific SMEsto resolve data history source ownership context and metadata gaps

• Differentiate between new / well-annotated data and legacy / incomplete dataapplying 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 curationsupporting both Biologics Engineering and Small Molecules domains

• Applyappropriate ontologies standardized formats and metadata taggingto support cross-domain reuse and AI/ML consumption

• Partner with domain scientiststo resolve data quality completeness and annotation gaps prior to transfer

Workflow Management & Process Improvement

• Prepare structured evidence packagesfor Data Owners Data Stewards and designated approvers so requests are decision-ready before formal review

• Track the interim data sharing processfrom intake through approval transfer execution validation and closure

• Act as process coordinator / trackerduring transfer execution following up on dependencies and ensuring documentation is complete without taking over technical execution tasks

• Capture recurring issues requirements and control pointsfrom the interim process to support the design of a future integrated data sharing solution

• Improve templates checklists trackers SOP inputs and audit-readiness practicesover time

Cross-Functional Partnership & Training

• Work with the R&D Data Officetoidentifywhat data is likely in scope or out of scope across different workstreams

• Partner with Privacy and Complianceto 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 safetyand how data is stored annotated accessed and extracted from separate systems

• Provide guidance to business and scientific teamson transfer readiness expectationsmetadata and supporting information

• Reduce ad hoc burden on scientists and business teamsby 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 experiencein pharmaceutical or biotech R&D data environments typically4 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)

• Coreexpertise: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 escalatetoLegal

• DOJ EO 14117 familiarity:Working understanding of the DOJs 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 tojurisdictions 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 able to translate between technical data needs and compliance requirements

• Problem-solving:Ability toidentifyalternative access patterns minimization strategies and creative solutions when straightforward transfer is restricted

• Systems literacy:Enough familiarity with data platforms to understand how data is stored what metadata exists and how to assess data content without requiring deep technical data engineering skills

China / Cross-Border Context

• China data classification: Familiarity with Chinas DSL data classification framework and what obligations apply to data once it enters China is preferred

• Global matrixed environment:Ability to work effectively across China and non-China stakeholders coordinating with US EU/UK and global teams on data access requests

Mindset

• Comfortable with ambiguity:Regulatory frameworks are evolving (particularly DOJ implementation guidance); this role will often work with emerging interpretations grey areas and imperfect precedent

• Low ego high impact:Willing to do detailed threshold calculationsjurisdictionmapping and documentation work that enables better decisions at scale

• Enablement-oriented:Approaches compliance as a problem to solve not a gate to close actively seeks minimization strategies alternative access patterns and creative compliant solutions to get researchers what they need

• Structured and practical:Able to turn regulatory requirements and fragmented information into a clear repeatable operating process

• Collaborative and credible:Able to work across scientific AI legal privacy and governance stakeholders with equal fluency

• Judicious and disciplined: Understands the difference between first-pass triage and final approval accountability

• Time zone flexibility:Comfortable working across US/UK and China hours as needed to support Beijing AI Center stakeholders

Desirable Skills/Experience:

• Education: PhD within relevant field

• Experience in both discovery-stage and later-stage R&D data environments

• Exposure to biologics omics sequence data compound data imaging data AI/ML training datasets or safety/pharmacovigilance data

• Direct experience operationalizing DOJ EO 14117 or similar US national security data restriction frameworks

• Experience with privacy-enhancing technologies (pseudonymization tokenization synthetic data federated learning secure computation) as transfer alternatives

• Experience with secure research environments data clean rooms or federated access architectures as alternatives to full data replication

• Experience supporting audit preparation SOP development or workflow/process redesign

• Experience in China-facing R&D operations or global roles thatroutine coordination on inbound data access for China-based teams

Call to Action:

If you are motivated to convert complexity into clarity and create the compliant data pathways that fuel next-generation discovery we would love to hear how you will make this impact with us!