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) [Principal CDS | PDF]

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