AI & Automation Scientist, Patient Safety

Job Title: AI & Automation Scientist – Patient Safety

Introduction to role

Are you ready to revolutionize patient safety with cutting-edge AI and automation? As an AI & Automation Scientist, you'll be at the forefront of transforming how we understand and support patients throughout their healthcare journey. Join us in creating a future where medicine goes beyond traditional boundaries, leveraging technology to enhance patient outcomes and experiences.

The AI & Automation Scientist – Patient Safety will play a critical role in advancing patient safety insights by automating structured analysis of data from clinical trials, internal and external safety databases, literature and real-world data. Using statistical, visual analytics, and AI/ML modeling techniques the role will develop and implement  data science workflows that evolve into  rules-based automation and AI agent tasks. Key responsibilities include data preparation   (structured and unstructured) application of advanced modelling algorithms and delivery of insights with clear interpretation and recommendations. The role will work directly with stakeholders in the patient safety (PS) organization to identify priority safety problems, design the appropriate workflow strategy and validate tools to ensure they are fit-for-purpose. This role will partner with drug projects and other colleagues in our R&D organization to support pharmacovigilance analysis and health authority questions. You will possess a blend of AI and data modeling skills with scientific domain knowledge.  She/he will also be delivery focused and have commercial ‘nous’ to tailor the analytics approach to the business need and context to achieve optimal results. 

Accountabilites:

• Develop and implement analytic solutions to address patient safety problems using statistics, machine learning, and visualization skills to deliver key insights from data or build self-service tools. 

• Collaborate closely with Patient Safety teams to develop an understanding of priorities and early insight into changing needs 

• In partnership with Patient Safety teams, translate unstructured and complex safety questions into the appropriate data science problems, predictive models, statistical tests, and analytical solutions 

• Apply data wrangling by extracting, transforming, cleaning, and integrating relevant data for model development  

• Apply best practices in programming (documentation, validation, version control, etc).   

• Implement right methods for data analysis and interpret the results in close partnership with PS stakeholders 

• Leverage knowledge of public and proprietary content sources to design complex search strategies that support regulatory, pharmacovigilance and drug safety experts. 

• Act proactively and reactively to respond rapidly to safety related queries from internal colleagues and external partners including Regulators.