Evidence Partnerships & Solutions, Director

Key Responsibilities 

• Drive identification, implementation and scaling of strategic partnerships (data, academic, medical societies) and technology solutions (infrastructure, software, AI, data networks, federated platforms) to accelerate Real-World and clinical trial evidence aligned with business priorities. 

• Execute innovative methodologies (e.g RWD to RCT linkage; implementation science; synthetic data) and digital tools to enhance evidence generation impact and scalability.

• Identify and recommend fit-for-purpose RWD based on hands-on assessment of relevance and reliability to address specific research questions that support product access and adoption.  

• Translate evidence generation needs into fit-for-purpose requirements and relevant solutions in collaboration with cross-functional teams. 

• Connect internal and external stakeholders to ensure consistent implementation of advanced solutions such as advanced statistical methods and ML/AI algorithms.  

• Collaborate with research, academic, industry and startups partners to stay at the forefront of Evidence Generation innovation.  

• Promote a culture of innovation to adopt novel scientific methods including pragmatic studies and hybrid trial models and creative ways to use data and technology solutions.  

• Develop and communicate data and technology learning content and toolkits to support new evidence capabilities across global teams .

• Ensure partnered research meets regulatory, legal, and ethical standards while maintaining high data quality and integrity. 

 What You’ll Bring to the Role  

• Experience in pharmaceutical, academic research, or healthcare settings with a focus on evidence generation. 
• Experience creating and fostering meaningful external supplier, academic, and non-profit partnerships to enhance evidence generation .
• Proven expertise in designing and executing interventional and non‑interventional studies and real‑world evidence approaches.
• Knowledge in RWD sources, common data models, Data Quality, FHIR, Tokenization, AI/GenAI, LLMs, ML modelling.
• Strong understanding of drug development with the ability to lead cross‑functional evidence initiatives. 
• Demonstrated ability to learn new scientific areas, tools, and advanced evidence methodologies. 
• Ability to create and implement innovative strategies that enhance evidence capabilities. 
• Strong communication skills with the ability to explain complex scientific concepts to diverse stakeholders. 
• Strong understanding and experience working across regions with knowledge of global regulatory, data privacy, and healthcare environments.