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AI Data Science Analyst
Jazz Pharmaceuticals. Support the design, development and implementation of AI/ML/GenAI/Agentic AI solutions to optimize clinical trial execution and R&D workflows .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI/ML solutions, particularly in the context of clinical trial execution and R&D workflows. Proficient in Python and SQL, with a solid understanding of data science principles and generative AI applications.
Highest-signal resume keywords
AI/ML Solution DevelopmentPython ProgrammingGenerative AI ConceptsModel EvaluationRegulatory Compliance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLData PreparationModel EvaluationGenerative AIMachine LearningAI Tools ApplicationPrompt EngineeringAgentic WorkflowsHigh Compute Cloud Platforms
Industry Keywords
Clinical Trial ExecutionR&D WorkflowsDrug Development LifecycleClinical DevelopmentAutomated Documentation Workflows
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- Support the design, development and implementation of AI/ML/GenAI/Agentic AI solutions to optimize clinical trial execution and R&D workflows
- Support the development and implementation of GenAI applications for automated clinical trial documentation workflows, including protocols, clinical study reports and SAPs
- Support model evaluation and quality testing to assess the accuracy, relevance, consistency and usability of generative AI outputs
- Ensure compliance with regulatory requirements and privacy standards
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or a related discipline, plus at least one year of relevant professional experience; or at least three years of relevant professional experience without a bachelor’s degree
- Programming skills in Python, SQL or similar languages
- Understanding of core data science and machine learning concepts, including data preparation, model evaluation and responsible use of AI
- Familiarity with generative AI concepts, including LLMs, prompt engineering, RAG and agentic workflows
- Experience in supporting the application of AI tools to automate, streamline or improve business, scientific or documentation-related workflows
- Familiarity with high compute cloud-based platforms and services
- Relevant experience may include internships or professional roles involving generative AI or AI-enabled automation
- Knowledge of the drug development lifecycle including clinical development is a plus
Benefits
Comp & perks- Medical, dental and vision insurance
- Retirement savings plan
- Flexible paid vacation