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. Computer Futures is part of the larger SThree group, the global STEM-specialist talent partner. To find out more about Computer Futures, please visit www.computerfutures.com | Computer Futures についてもっと詳しく知りたい方はこちらへ→ www.computerfutures.com Award winner of: The IT and Technology Recruitment Company of the Year by TIARA Awards 2018 | Best Large Company to Work For by TIARA Awards 2021 | Best CSR Initiative by TIARA Awards 2019 | Best Workplace by Great Place to Work Institution 2019, 2021, 2022 & 2023.