Lead, R&D Data Transformation & AI Readiness

Astrazeneca Plc

Laza

Presencial

EUR 90.000 - 140.000

Jornada completa

Hace 3 días

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Descripción de la vacante

AstraZeneca PLC is seeking an Associate Director, R&D Data Transformation to lead transformation initiatives that improve data readiness, interoperability, and reuse across the R&D data estate. You will own end-to-end workstreams, coach junior team members, and collaborate with R&D functions to enable AI-ready data for science innovation.

Lead design and delivery of data readiness, interoperability, and reuse programs, applying FAIR principles and industry standards to advance

Formación

Degree in life sciences, informatics, data science, or a related discipline, or equivalent professional experience.
Significant experience delivering data transformation, data strategy, or data management initiatives within complex, global organisations; ideally within pharmaceutical R&D or a highly regulated scientific environment.
Demonstrated success designing and executing transformation initiatives with measurable improvements in data quality, interoperability, or reuse.
Strong knowledge of data management principles, FAIR standards, metadata management, and ontology frameworks, with the ability to apply these practically in scientific data environments.
Proven ability to influence stakeholders across technical and scientific functions; skilled in translating complex data concepts into clear recommendations and actionable plans.
Experience coaching or mentoring junior colleagues, with a track record of supporting capability development and maintaining quality standards across team deliverables.
Strong analytical and problem-solving skills with the ability to manage competing priorities and drive outcomes with limited supervision.
Knowledge of pharmaceutical drug discovery and development processes, including data flows across preclinical, clinical, regulatory, and manufacturing domains.
Familiarity with AI/ML data requirements and experience enabling data readiness for advanced analytics and machine learning use cases.
Experience with enterprise data platforms or cloud-based data ecosystems (e.g., Databricks, Snowflake, AWS/Azure data services).
Experience with data cataloguing tools, metadata management platforms, or knowledge graph technologies.
Experience applying change management principles or behavioural science approaches to drive adoption of new data practices and standards.

Responsabilidades

Own and deliver end-to-end transformation workstreams — from current-state assessment and gap analysis through solution design, implementation, adoption, and sustainment.
Apply the transformation methodology (maturity models, prioritisation criteria, delivery playbooks) within assigned workstreams, contributing to its continuous improvement based on practical experience and lessons learned.
Conduct assessments of R&D data domains to evaluate readiness, interoperability, and reuse maturity; produce actionable recommendations with clear sequencing and dependencies.
Partner with data domain owners, scientists, and R&D functional teams to co-design solutions that address specific readiness, interoperability, and reuse gaps within assigned scope.
Monitor and manage risks, issues, and dependencies within assigned workstreams; contribute to stage-gate reviews and deliver post-implementation evaluations.
Coach and mentor junior team members (Manager level), providing technical guidance, quality assurance on deliverables, and support for professional development.
Share knowledge and specialist expertise across the R&D Data Transformation team, contributing to methodological consistency and collective capability development.