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)
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
- Pharma Supply
Represents BI regarding:
- Clinical planning
- Data transformation
- Statistical analyses
- Critical regulatory requests
- Project and asset-level data science activities
Experience & Expertise
Required:
Data Science Expertise
- Strong understanding and application of data science principles
- Broad expertise in:
- Planning analyses
- Data transformation
- Statistical analysis
- Interpretation of results
- Reporting
Technical Expertise
- Broad knowledge and advanced experience in relevant programming/software languages
Clinical Development Expertise
- Advanced understanding of the clinical drug development lifecycle
- Strong understanding of clinical trial development
Leadership
- Advanced project leadership experience required
Experience Requirements
PhD: 3+ years in pharmaceutical industry, CROs, regulatory authorities, or academia
MSc: 6+ years in pharmaceutical industry, CROs, regulatory authorities, or academia
Bachelor's Degree: 7+ years of data science experience
Deep subject matter expertise may partially compensate for experience requirements.
Job Impact
Responsible for:
- Analysis of clinical drug lifecycle data
- Delivering scientific insights to internal and external stakeholders
- Independent decision-making related to data science activities
- Translating data into business and scientific value
Results must be tailored to customer and stakeholder needs.
Education Requirements
Bachelor's, Master's or Doctoral degree in:
- Statistics
- Mathematics
- Computer Science
- Data Science
- Psychology
- Finance
- Related quantitative disciplines
Required Capabilities
Statistical & Scientific Expertise
- Thorough knowledge of statistical methodology
- Strong understanding of experimental design and clinical trials
- Understanding of terminology related to supported disease areas and assets
- Experience processing clinical trial information
Advanced Analytics
- In-depth understanding of advanced statistical concepts used in Data Science
Technical Skills
- Advanced working knowledge of multiple relevant software/programming languages
Leadership & Training
- Ability to lead and facilitate meetings
- Ability to develop and deliver data science training
- Strong project leadership capability
Communication
- Fluent English (Read / Write / Speak)
- Strong communication and presentation skills
Collaboration
- Proven ability to work within global and remote teams
- Strong stakeholder management skills
- Effective collaboration with CROs, experts and management
Problem Solving
- Proactively identify issues
- Develop solutions
- Interact independently with internal and external stakeholders on data science matters
Cultural Awareness
- Effective communication across local and global cultures
- Sensitivity to internal and external stakeholder needs
Quick Candidate Snapshot
- PhD + 3 years, MSc + 6 years, or Bachelor's + 7 years of relevant Data Science experience
- Strong statistical analysis and programming expertise
- Experience with clinical trial, registry and/or real-world data
- Strong understanding of pharmaceutical R&D and clinical development
- Advanced project leadership experience
- Experience driving innovation and digital transformation
- Strong stakeholder management and data storytelling capabilities
- Fluent English communication skills
