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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy predictive modeling, ML, and AI solutions addressing clinical development challenges including trial execution and patient analytics.
Conduct statistical analyses and data exploration on clinical trial data, EHR/EMR, and real-world evidence to generate actionable insights.
Collaborate with clinical and operational stakeholders to translate complex data into structured analytical frameworks and communicate findings effectively.
Minimum Requirements
5+ years of progressive experience in data science or ML engineering, preferably with biopharma, pharma, or clinical research exposure.
Proficiency in Python, PySpark, or R with experience in clinical and statistical packages and ML frameworks.
Hands-on experience with AI/GenAI technologies including LLMs, RAG frameworks, Agentic AI, and prompt engineering.
Bachelor’s, Master’s, or Ph.D. in Data Science, Statistics, Biostatistics, Computer Science, or related discipline.
Ideal Candidate Profile
Demonstrated ability to deliver end-to-end analytical or ML solutions in regulated clinical environments involving clinical trial and RWD data.
Experienced in building efficient data pipelines and applying MLOps/GitOps practices within cloud environments (AWS/Azure, Spark, GitHub).
Skilled in integrating AI/GenAI tools into clinical workflows and familiar with clinical drug development lifecycle and regulatory contexts.