Clinical Science Data and AI Lead

Major accountabilities:

• Lead data and AI projects in DDCI team

• Actively lead or participate in the identification of data gaps for 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

  • 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

• 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

Key performance indicators:

• Data and AI projects addressing clinically relevant needs or providing value-based solutions

• Data and AI strategies implemented in CDPs; support timely submission and delivery of high quality data supporting internal decision making, strengthening evidence package for regulatory approvals, as appropriate

• Collaboration and effective partnerships with data science groups to execute on project priorities

• Effective interaction with and influence on key internal, external decision makers (e.g. management boards, regulatory authorities, medical experts etc) as applicable

Minimum Requirements:

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

• Fluency in English (spoken & written)

• ≥ 7 years of involvement in clinical research or drug development in an academic or industry environment.

•  ≥ 5 years of contribution to and accomplishment in all aspects of data science, in a global/matrix environment in pharmaceutical industry

• 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 on 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.

• Ability to work, gain trust and influence at all levels of the organization.

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

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

• Coach/lead people: inspire and empower others to be strong leaders.

• Ability to work independently without significant direction and guidance.