Director, Clinical Science Data & AI Lead

Role Purpose

• Initiate and Lead data and AI projects in DDCI team and represent DDCI within the clinical development team

• Lead and manage a team of data scientists and analysts to drive data-driven decision-making processes

• Have a strategic mindset and the ability to align data science initiatives with broader business goals. possess a deep understanding of the organization's industry, market trends, and competitive landscape to provide insights that contribute to strategic decision-making.

• Actively lead the identification of data scientific and clinical needs in clinical development in one or more therapeutic areas, and in the development and implementation of strategic solutions to these gaps, e.g.

  • Evaluate the data quality from internal and external data sources for DDCI projects 

  • Collaborate with internal stakeholders to bring in external data to internal data platform

  • Evaluate and implement AI solutions to improve the efficiency and effectiveness of clinical development programs, including hands-on computational model development and application

  • Collaborate with data science groups to support the implementation of use cases and help identify work flows and techniques that may be reproducible

  • Bridges scientific, technical, and drug development expertise to engage with clinical leads in CD, program teams, disease units,  analytics, regulatory and commercial for data science and AI  approaches

  • Enables the evaluation, internalization, validation and piloting of novel advanced external technologies.

• Partner with Analytics and other Data Science organizations to plan and implement training and coaching in order to drive a culture of data and AI literacy and innovations to drive clinical development success.

• Track data science and AI projects within DDCI requiring inputs and support

• Scope and evaluate data science and AI technology solutions for drug development 

• Ensure data transformation and analysis specifications to ensure completeness, correctness and adherence to department guidelines and SOPs as well as to applicable GxP requirements

• Manage relationships with external vendors and partners for data-related projects.

• Mentor and develop team members, fostering a culture of continuous learning and growth.

• Communicate findings, recommendations, and insights to executive leadership and other stakeholders

Requirements:

• PhD (essential), Post Doc (desired) in data science, biostatistics, computational biology, bioengineering or related field

• Fluency in English (spoken & written)

• ≥ 10 years of involvement in clinical research or drug development in an academic or industry environment.

•  ≥ 7 years of contribution and/or leadership and accomplishment in all aspects of data science and associated applications for development programs, in a global/matrix environment in pharmaceutical industry

• Significant experience in data science, machine learning, and analytics, with a proven track record of implementing successful data strategies and delivering impactful insights

• Experience in leading and managing teams of data scientists, analysts, and other data professionals, as well as working with external partners

• Possess a strong business acumen, including a solid understanding of how data analytics can drive value and impact business outcomes. They should be able to effectively communicate data-driven insights and recommendations to non-technical stakeholders, influencing decision-making across the organization

• Excellent interpersonal and communication skills (written and verbal), presentation.

• Excellent analytical, process-oriented and data driven mind- set..

• Coach/lead people (a plus): inspire and empower others to be strong leaders.

• Demonstrated ability to establish strong scientific partnership with key stakeholders

• Thorough knowledge of GCP, clinical trial design, statistical analysis methodology, and regulatory/clinical development process

• Scientific background in basic and clinical research with good understanding and knowledge of drug development.

• Strong skills in leading and managing cross-functional projects with significant (visible) business impact.

• Proficient in Python, SAS, R, and R-shiny; Building machine learning models utilizing high performance computing (HPC) environments

• Significant experience, and proven ability to effectively engage, manage and influence associates from widely varying backgrounds & functions within a dispersed and highly matrixed organization.