Head Clinical AI Strategy
Healthcare
HeadClinicalAIStrategyTranslationalResearch
“Head Clinical AI Strategy - Translational Research at Head Clinical AI Strategy. Skills: Clinical AI Strategy, Translational Research, Data Science, AI. Direct strategic roadmap of Data Science & AI. Implement strategic roadmap of Data Science & AI”
What You'll Achieve.
Deliver high-value AI solutions; Improve scientific understanding; Improve trial design; Improve development decisions; Quantify value of work; Accelerate AI capability development
Industry & Context.
Scientific questions; Data-driven decision making
What They're Looking For.
Must Have
Advanced degree (PhD, MD, MSc) in relevant scientific fields, Minimum 10 years of relevant experience in pharmaceutical settings, Demonstrable track record of delivering global solutions at scale in healthcare settings, Experience integrating scientific, data-science, and operational perspectives in R&D, Experience in defining KPI and ROI frameworks, Proven experience developing and implementing digital or AI strategy in a complex, matrixed organization, Understanding of AI/ML methodologies in biomedical contexts, Excellent English required (oral & written)
Nice to Have
PhD or equivalent experience in Data Science, Computer Science, or related field, Experience in the drug development space
What You'll Do.
Direct strategic roadmap of Data Science & AI
Implement strategic roadmap of Data Science & AI
Integrate scientific questions
data-science methodologies
and operational execution
Ensure delivery of AI solutions for Translational Medicine
Ensure delivery of AI solutions for Biomedical Research
Integrate scientific needs into strategies
Convert clinical needs into strategies
Incorporate data science solutions into strategies
Incorporate operational execution into strategies
Incorporate KPIs into strategies
Incorporate ROI assessments into strategies
Incorporate value frameworks into strategies
Show how AI implementation improves scientific understanding
Show how AI implementation improves trial design
Show how AI implementation improves development decisions
Serve as bridge between scientific leaders and data-science
Decipher scientific questions into AI use-cases
Articulate scientific questions into AI use-cases
Identify high-value AI use cases
Shape high-value AI use cases
Support governance processes
Support decision-making processes
Prepare content for meetings
Communicate proposals to stakeholders
Build actionable delivery plan for endorsed use cases
Oversee delivery of endorsed use cases
Oversee assessment of endorsed use cases
Oversee development of BR Clinical Design Lab
Enable scaled implementation of data driven solutions
Enable scaled implementation of AI solutions
Enable process optimized implementation of data driven solutions
Enable process optimized implementation of AI solutions
Define impact measurements
Develop impact measurements
Track impact measurements
Quantify value of work at trial level
Quantify value of work at program level
Assess data landscape supporting clinical development AI work
Enable fit-for-purpose data availability
Evaluate technology vendors
Recommend strategic partnerships
Recommend collaborations
Accelerate AI capability development
Promote awareness for AI-driven processes
Promote adoption for AI-driven processes
Promote change management for AI-driven processes
Foster understanding organization-wide
Demonstrate internal presence
Demonstrate external presence
Bring recognition of Novartis as leader in Data
Bring recognition of Novartis as innovator in Data
Bring recognition of Novartis as leader in AI
Bring recognition of Novartis as innovator in AI
Serve as strategic thought partner to clinical leadership
Provide insights on AI enablement
Provide advice on AI enablement
Provide insights on scientific value
Provide advice on scientific value
Provide insights on emerging trends
Provide advice on emerging trends
How You'll Work.
Team & Collaboration
With scientific leaders; With data-science teams; With clinical teams; With partners in Data & Digital; With Data Science teams; With enterprise partners; With clinical leadership teams
Communication Scope
Stakeholder engagement; Influencing; Communication
Process & Methodology
Program Management
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