Responsibilities:

• Lead the deployment of automation technologies to streamline the creation and updating of mandatory materials.
• Conduct thorough evaluations of automation technologies tailored to pharmaceutical documentation needs.
• Prioritize vendors with relevant experience and technical expertise in automation projects.
• Develop clear implementation plans outlining scope, timeline, and resource requirements for testing automation solutions.
• Supervise the successful piloting of automation solutions and closely monitor performance.
• Utilize advanced language models to automate FAQ creation from scientific articles.
• Train language models using existing FAQs and scientific literature from databases.
• Establish systems for automatic generation and review of FAQs to reduce manual effort.
• Design algorithms to extract insights and summaries from detailed call notes captured by the Medical Science Liaison team.
• Apply data science techniques to analyze verbatim discussions and identify critical signals and trends.
• Collaborate with team members to translate medical insights captured by MSL into actionable strategies.
• Continuously improve data science models based on feedback and evolving needs.

Detailed Responsibilities:
Automation Integration for Pharmaceutical Documentation:

• Assess available automation technologies tailored to pharmaceutical documentation needs.
• Evaluate solutions based on data extraction efficiency, natural language processing capabilities, and compatibility with existing systems.
• Prioritize vendors with experience in similar automation projects.
• Develop a comprehensive implementation plan, including scope, timeline, and resource requirements.
• Oversee successful piloting of automation solutions, monitoring performance and gathering feedback for optimization.
• Scale automation solutions to encompass all mandatory documents for creation and updates.

FAQ Creation Using Advanced Language Models:

• Utilize advanced language models, such as GenAI, to automate FAQ creation from scientific articles.
• Train language models using existing FAQs and scientific literature from databases like Pubmed or Embase.
• Implement systems for automatic generation and review of FAQs to improve efficiency.
• Ensure accuracy and relevance of generated FAQs through continuous monitoring and refinement.

Data Science for Medical Science Liaison (MSL) Insights:

• Develop algorithms to extract insights and summaries from detailed call notes captured by the MSL team.
• Use data science techniques to analyze and interpret verbatim discussions, identifying key signals and trends.
• Collaborate with MSL team members and managers to translate raw medical voice of customer into actionable insights.
• Design algorithms to evaluate insights with a quality index.
• Implement automated processes to streamline insight generation and assessment.
• Continuously refine and enhance data science models based on feedback and evolving requirements.