AstraZeneca
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 will 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.
Key Responsibilities The AI & Automation Scientist – Patient Safety will play a critical role in advancing patient safety insight 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 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 and a commercial focus to tailor the analytics approach to the business need and context to achieve optimal results.
Accountabilities
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.
Familiar with the challenges related to handling sensitive clinical information in compliance with governance and regulatory standards.
Essential Requirements
BSc/MSc/Ph.D. degree in medical, life sciences, computer science, applied statistics, or related quantitative field.
Ability to learn fast and implement analytics solutions by selecting the right set of tools.
Experience utilizing automation and AI agent tools such as Microsoft Power Automate and Microsoft Copilot Studio.
Experience with visual analytics tools including Power BI.
Functional expertise in programming, especially Python, SQL, git and AI‑powered command‑line interfaces such as Claude Code or Codex CLI.
Experience using a testing‑harness to drive LLM prompt development.
Strong understanding of AI/ML concepts, general methodologies, and the AI development lifecycle, sufficient to enable effective leadership of, and collaboration with, technical AI teams, data scientists, and technology vendors.
Proven record of implementing analytical solutions to address research/business problems.
Experience of working in a matrix environment with multiple stakeholders.
Outstanding communication, presentation, and interpersonal skills, with a proven ability to convey complex medical and technical information clearly to diverse audiences, including senior leadership.
Desired
Experience in data visualization techniques addressing complex data sets, especially on clinical data using ADaM and SDTM data formats.
Experience in pharmacovigilance, clinical safety, or a closely related medical field within the pharmaceutical industry or a regulatory agency.
Highly developed analytical and conceptual thinking, with the ability to understand multiple, complex business needs and to prioritize them.
Experience with system validation, data governance, data privacy, and cybersecurity considerations relevant to AI in a regulated (GLP, GCP, GVP, etc.) industry setting.
Proven ability to critically evaluate AI/ML methodologies and outputs including assessing from a clinical and patient safety perspective for potential utility, biases, and safety implications.
Experience in working across different geographic locations, organizations, and cultures.
Exerting influence without authority.
Application Dates Date posted: 17-Oct-2025 Closing date: 09-Nov-2025
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.
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Introduction to role Are you ready to revolutionize patient safety with cutting‑edge AI and automation? As an AI & Automation Scientist, you will 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.
Key Responsibilities The AI & Automation Scientist – Patient Safety will play a critical role in advancing patient safety insight 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 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 and a commercial focus to tailor the analytics approach to the business need and context to achieve optimal results.
Accountabilities
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.
Familiar with the challenges related to handling sensitive clinical information in compliance with governance and regulatory standards.
Essential Requirements
BSc/MSc/Ph.D. degree in medical, life sciences, computer science, applied statistics, or related quantitative field.
Ability to learn fast and implement analytics solutions by selecting the right set of tools.
Experience utilizing automation and AI agent tools such as Microsoft Power Automate and Microsoft Copilot Studio.
Experience with visual analytics tools including Power BI.
Functional expertise in programming, especially Python, SQL, git and AI‑powered command‑line interfaces such as Claude Code or Codex CLI.
Experience using a testing‑harness to drive LLM prompt development.
Strong understanding of AI/ML concepts, general methodologies, and the AI development lifecycle, sufficient to enable effective leadership of, and collaboration with, technical AI teams, data scientists, and technology vendors.
Proven record of implementing analytical solutions to address research/business problems.
Experience of working in a matrix environment with multiple stakeholders.
Outstanding communication, presentation, and interpersonal skills, with a proven ability to convey complex medical and technical information clearly to diverse audiences, including senior leadership.
Desired
Experience in data visualization techniques addressing complex data sets, especially on clinical data using ADaM and SDTM data formats.
Experience in pharmacovigilance, clinical safety, or a closely related medical field within the pharmaceutical industry or a regulatory agency.
Highly developed analytical and conceptual thinking, with the ability to understand multiple, complex business needs and to prioritize them.
Experience with system validation, data governance, data privacy, and cybersecurity considerations relevant to AI in a regulated (GLP, GCP, GVP, etc.) industry setting.
Proven ability to critically evaluate AI/ML methodologies and outputs including assessing from a clinical and patient safety perspective for potential utility, biases, and safety implications.
Experience in working across different geographic locations, organizations, and cultures.
Exerting influence without authority.
Application Dates Date posted: 17-Oct-2025 Closing date: 09-Nov-2025
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.
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