Senior Director, Clinical Data Intelligence & Medical Monitoring Innovation

Job Description
The Senior Director, Clinical Data Intelligence & Medical Monitoring Innovation is responsible for leading business-facing digital and visual analytics, and AI-driven initiatives that modernize clinical data review and medical monitoring within Clinical Development.
Reporting directly to the Senior Director, Head of Clinical Development Learning & Center of Excellence (CoE), this role serves as the strategic bridge between advanced technological capabilities and clinical practice across all therapeutic areas. The primary mission of this role is to drive organizational change management to modernize how study teams review data, monitor patient safety, identify clinical signals, and make real-time decisions using visual analytics and AI-enabled technologies.
This role partners closely with the Heads of Clinical Science (Oncology and Non-Oncology), Clinical TA Leadership, and other key functions such as Data Management, Biostatistics, Statistical Programming, Digital, Data Science, Artificial Intelligence, and Information Technology to define business needs, set priorities, and support delivery of solutions that are practical, compliant, and scalable.
In this capacity, the individual represents Clinical Development in cross-functional forums, collaborating with digital and IT partners to ensure that technical and AI-driven solutions are aligned with the workflows and scientific needs of clinical scientists and clinical directors.
The ideal candidate is an expert, former Clinical Scientist with a minimum of 5 years of hands-on experience in clinical trial design, clinical data review, medical monitoring and execution, combined with deep technical expertise in data visualization, technological innovation and AI, and a passion for teaching these capabilities to others. The successful candidate will be expected to identify opportunities to improve current processes, translate user needs into clear requirements, support implementation of new capabilities, and drive adoption across Clinical Development.
Key Responsibilities:
Business Leadership
Serve as the Clinical Development business lead for digital, analytics, and AI-enabled capabilities that support clinical data review and medical monitoring.
Identify and prioritize opportunities where visual analytics, automation, AI, and related digital capabilities can improve patient safety oversight, scientific quality, operational efficiency, and decision-making.
Partner with Clinical Science leadership and study teams to understand process gaps, user needs, and opportunities for improvement.
Ensure proposed solutions address clear business problems and provide measurable benefit to study teams.
Clinical Data Review and Medical Monitoring
Lead efforts to improve how clinical data are reviewed, with a focus on usability, consistency, quality, and timeliness.
Drive implementation of modern visual analytics and data review capabilities to support earlier identification of safety signals, efficacy trends, protocol deviations, data quality issues, and operational risks.
Work with Clinical Scientists, Clinical Directors, and study teams to identify opportunities to improve medical monitoring workflows and supporting tools.
Support the transition from static reports and manual review processes to more interactive and risk-based approaches where appropriate.
Help define use cases for visual analytics, automated workflows, and other capabilities that support earlier identification of safety issues, efficacy trends, protocol deviations, operational issues, and data quality concerns.
Ensure solutions support appropriate medical and scientific review and are fit for use in a regulated environment.
Partnership with Head of Clinical Development Learning
Partner with the Senior Director, Head of Clinical Development Learning to ensure new tools, analytics capabilities, and digital ways of working are supported by appropriate training, communication, and change enablement.
Provide clear guidance on what users need to understand and be able to do in order to effectively adopt new capabilities.
Collaborate on change management strategies that support sustained adoption, including input on timing, sequencing, user readiness, and communication of new capabilities.
Support the Center of Excellence team with subject matter content, demonstrations, and technical context needed to develop effective training and learning materials.
Ensure implementation plans for new capabilities account for organizational readiness and are coordinated with learning and adoption activities.
Cross-Functional Collaboration
Represent Clinical Interests: Act as a key partner representing Clinical Development workflows and scientific requirements in cross-functional technological, digital, or AI-driven initiatives.
Promote User-Centric Design: Partner with enterprise IT and Digital organizations to ensure tools are fit for clinical purpose, user-friendly, and streamlined to support efficient clinical workflows.
Cross-Functional Influence: Partner with senior leaders in Data Management, Biostatistics, Statistical Programming, Digital, IT, and AI/Data Science to align technical roadmaps with Clinical Development’s operational and scientific reality. Support prioritization and trade-off discussions across functions to align resources and delivery plans.
Implementation and Adoption
Support implementation of new tools and capabilities across Clinical Development.
Develop plans for stakeholder engagement, communications, training, and adoption tracking.
Work with end users to gather feedback, assess effectiveness, and identify opportunities for refinement.
Promote consistent use of approved tools and processes across studies and programs.
Share lessons learned and leading practices across teams to improve consistency and efficiency.
Governance and Continuous Improvement
Support appropriate governance, validation, documentation, and oversight for new capabilities, including AI-enabled solutions where applicable.
Monitor external developments in clinical data review, medical monitoring, analytics, and AI to inform future planning.
Establish and track measures of success related to adoption, quality, efficiency, and user experience.
Identify opportunities for continuous improvement and help build longer-term plans for capability development within Clinical Development.
People Management & Team Leadership
Direct the Innovation Team: Provide strategic direction, line management, coaching, and professional development for direct reports.
Resource Allocation: Oversee the team’s project portfolio, aligning innovation efforts with therapeutic area clinical pipelines and CoE strategic priorities.
Cultivate Technical Excellence: Foster a high-performing culture of scientific curiosity, technical expertise, and collaborative problem-solving within the team.
Essential Leadership Skills
Identifies emerging opportunities and translates innovative ideas, analytics, and AI-enabled capabilities into practical solutions that improve patient safety oversight, scientific quality, and operational effectiveness.
Aligns digital and analytics priorities with Clinical Development objectives, balancing long-term capability building with near-term business needs and measurable outcomes.
Builds strong cross-functional relationships and effectively influences stakeholders across Clinical Development, Data Management, Biostatistics, Statistical Programming, Digital, Data Science, AI, IT, and Quality to achieve shared objectives.
Leads adoption of new capabilities and ways of working by creating alignment, overcoming resistance, and fostering sustained organizational change across Clinical Development.
Promotes a culture of continuous improvement by advancing new approaches to clinical data review, medical monitoring, visual analytics, automation, and digital enablement.
Drives execution with clear accountability, ensuring that capabilities are implemented effectively, governance requirements are met, and business value is realized.
Educational Requirements:
Required (one of the following combinations):
Doctoral degree (PhD, PharmD, or equivalent scientific/ clinical degree) plus 8 years of combined relevant experience, of which at least 5 years must be within pharmaceutical or clinical development environments.
OR
Master's degree in Life Sciences, Biomedical Sciences, Data Science, Health Sciences, or related clinical/scientific field plus 12 years of combined relevant experience, of which at least 8 years must be within pharmaceutical or clinical development environments.
OR
Bachelor’s degree in Life Sciences, Biomedical Sciences, Data Science, Health Sciences, or related clinical/scientific field plus 15 years of combined relevant experience, of which at least 10 years must be within pharmaceutical or clinical development environments.
Required Experience: