Basic Purpose of the Job
Supports the complete clinical/pharmaceutical drug lifecycle process (research, development, market access, and market supply) through:
• Strategic planning and execution
• Data transformation
• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics
Works with data from:
• Clinical trials
• Clinical registries
• Real-world databases
Provides:
• Analytics tools
• Data outputs
• Scientific insights and inference
May act as an ExpMED Product Owner up to the substance/asset level and represent ExpMED on data science-related matters.
Key Accountabilities
Data Science Leadership
Responsible for:
• Leading and overseeing design, transformation, analysis and reporting for complex Phase I-IV clinical trials
• Supporting complex international projects
• Leading analysis of registry and real-world data
• Delivering data science solutions aligned with specific project and asset needs
Success Measures
• Quality deliverables
• Timeline adherence
• Feedback from development teams, Product Owners and capability managers
Innovation & Scientific Advancement
• Stay current on developments in data science both within and outside BI
• Convert insights into new data science approaches supporting:
• Discovery
• Clinical development
• Regulatory registration
• Manufacturing
• Commercialization
Success Measures
• Quality of innovative solutions
• Adoption of new processes and tools
• Stakeholder feedback
Data Storytelling & Communication
• Present compelling, validated stories based on complex data science findings
• Communicate effectively with scientific and non-scientific stakeholders
Success Measures
• Quality and frequency of presentations
• Audience understanding and feedback
Compliance & Data Quality
• Ensure data transformation and analysis specifications are:
• Complete
• Accurate
• SOP-compliant
• GxP-compliant
Success Measures
• Regulatory acceptance
• Quality of specifications
Coaching & Knowledge Sharing
• Guide and lead colleagues
• Support internal customers and external partners
• Promote knowledge sharing within the Clinical Data Science community
Success Measures
• Feedback from colleagues
• Increased knowledge sharing and capability development
Cross-Functional Leadership
• Participate in BI cross-functional working groups
• Lead One Human Pharma internal working groups
• Participate in external industry working groups
• Drive relevant data science initiatives
Success Measures
• Quality of leadership
• Business impact of working group outcomes
• Feedback from Global Product Owners and Product Owners
Product Owner Responsibilities
Where applicable:
• Support the clinical drug lifecycle process as an ExpMED Product Owner
• Provide leadership at product, substance and asset level
Success Measures
• Product quality
• Leadership effectiveness
• Timeline adherence
• Stakeholder satisfaction
Collaboration & Digital Innovation
• Promote cross-functional teamwork within ExpMED and across BI
• Support innovative digital solutions
• Drive predictive models and intelligent optimization approaches
• Contribute to organization-wide innovation initiatives
Success Measures
• Quality of collaboration
• Frequency of innovative digital initiatives
• Stakeholder feedback
Regulatory & Organizational Requirements
Must understand and implement:
Regulatory Requirements
• International Good Clinical Practice (GCP)
• Good Statistical Practice
• ICH guidelines and regulations across all regions
Clinical Development Requirements
• Statistical methodology guidance
• Clinical development standards
• Therapeutic Area-specific requirements
Internal Requirements
• BI processes
• Standard Operating Procedures (SOPs)
• Clinical Development Plan requirements
Additional Requirements (where applicable)
• Good Laboratory Practice (GLP)
• Good Manufacturing Practice (GMP)
Job Complexity
• Solves complex, defined problems
• Has strategic impact across the clinical drug lifecycle
• Considers the needs and requirements of multiple departments and stakeholders
• Influences decision-making at a broader organizational level
Interfaces
Collaborates with:
• GCO
• GPV
• Therapeutic Areas
• TMCP
• GRA
• Research
• Development