Develop and implement an AI strategy aligned with organizational goals.
Establish ethical AI governance frameworks.
Ensure regulatory compliance for AI deployments.
Conduct AI readiness assessments and change management initiatives.
AI-Powered Automation & Process Optimization:
Identify and automate manual processes in clinical, research, and administrative areas.
Deploy scalable, cloud-based AI solutions integrated with existing systems.
Optimize supply chain operations using AI-driven forecasting models.
AI for Data-Driven Decision-Making & Commercial Strategy:
Build predictive analytics models for patient risk assessment and disease prevention.
Support drug discovery, diagnostics, and clinical trial optimization.
Enable AI-driven insights for sales, marketing, pricing, and commercial forecasting.
Collaborate with Data Engineers to enhance data platforms and pipelines.
AI for Patient-Centric Innovation:
Design AI-powered patient tools (chatbots, and virtual assistants).
Develop personalized treatment models and remote monitoring solutions.
Advance telemedicine technologies to increase care accessibility.
Education:
Bachelors Degree in AI, Data Science, Computer Science, Healthcare Informatics, or related field.
Solid foundation in machine learning, AI, and data analytics.
Preferred:
Masters or PhD in a related discipline.
Certifications such as Google Cloud AI/ML, Azure AI Engineer, AWS ML Specialty, TensorFlow, IBM AI Engineering.
Experience & Skills:
Required:
35 years of experience in AI, machine learning, or data science.
Hands-on AI model development and deployment.
Experience in predictive analytics, sales forecasting, or business process automation.
Familiarity with cloud platforms, data engineering, and database management.
Preferred:
Exposure to healthcare or pharmaceutical industry standards.
Experience with AI in medical imaging, diagnostics, or clinical trials.
Knowledge of patient engagement technologies and personalized medicine.
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