Senior Clinical Data Science Lead

As a Senior Clinical Data Science Lead at ICON, you will lead the analysis, interpretation, and management of clinical data to drive the success of our clinical trials.

What You Will Do:

You will oversee clinical data science workstreams, ensuring deliverables meet quality and timeline expectations while acting as the functional lead across multiple low to moderately complex studies.

Key responsibilities include:

• Leading the development and implementation of clinical data management strategies to optimize data collection, analysis, data review, and reporting.
• Leading multiple low/moderately complex studies as the functional Clinical Data Science Lead and acting as a resource for colleagues with less experience.
• Collaborating with cross-functional teams to ensure the accurate integration of data science techniques into clinical trial designs.
• Overseeing the analysis and review of clinical data to provide actionable insights that inform study decisions and outcomes.
• Providing strategic guidance on data governance, quality control, and compliance with regulatory requirements.
• Establishing partnerships with key stakeholders to leverage the latest advancements in data science and technology in clinical research.
• Applying project management skills to proactively manage timelines, resource requirements, and financial tracking.
• Developing a detailed understanding of protocol content and interpreting critical data and data review requirements.
• Reacting and adapting requirements, processes, and timelines in an agile manner to meet project and business needs.
• Tracking study progress and keeping functional management and project management informed of issues that may affect project target dates, scope, or budget, escalating risks in a timely manner.
• Working independently and with other project leads, as needed, to negotiate timelines and key deliverables with clients, external customers, and internal departments.
• Understanding project-level revenue recognition and forecasting processes, providing input on actual and forecasted units/hours (revenue and resources) to the Clinical Data Science Project Manager.
• Undertaking other responsibilities as assigned.

Your Profile:

You will have solid clinical data science experience, with the ability to manage competing priorities, lead multiple studies, solve complex problems, and support the development of your team.

Required qualifications and experience:

• Bachelor's degree in life sciences, computer science, or a related discipline.
• Typically 5–8 years of experience in Clinical Data Science, Clinical Data Management, or a related field. An equivalent combination of education, training, and relevant experience may be considered in place of the stated education and experience.
• Extensive experience in clinical data science, with a strong focus on clinical data management, data review, and analysis in clinical trials.
• Enhanced knowledge of clinical data management, clinical data science, and clinical data review activities.
• Applied project management skills, including experience managing timelines, resource requirements, and financial tracking.
• Detailed understanding of protocol content and interpretation of critical data and data review requirements.
• Strong leadership skills and a proven ability to lead multiple studies, manage cross-functional teams, and act as a resource for colleagues with less experience in a fast-paced, matrix environment.
• Strong problem-solving skills with the ability to analyse and investigate complex issues, identify solutions that are not readily apparent, and anticipate future challenges.
• Ability to work independently, establish approaches, and lead resources to achieve operational and strategic objectives with impact on medium-term goals.
• Expertise in data analysis tools, statistical software, and data visualization techniques.
• Excellent communication, interpersonal, and stakeholder management skills, with the ability to adapt communication style, influence stakeholders, present and defend complex analyses, and secure approval on complex matters

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