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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy predictive models and AI/GenAI solutions to address clinical development challenges, including survival analysis, forecasting, and Monte Carlo simulations.
Conduct rigorous statistical analyses and exploratory data analysis on clinical trial, EHR/EMR, and real-world evidence data to provide actionable insights.
Collaborate with clinical and operational stakeholders to align on objectives, present findings, and maintain data pipelines and MLOps practices for scalable, reliable analytics solutions.
Minimum Requirements
5+ years of progressive experience in data science or ML engineering, preferably in biopharma, pharma, or clinical research.
Proficiency in Python, PySpark, or R including clinical/statistical packages and ML frameworks.
Experience working with clinical trial data, EHR/EMR, or real-world data sources with understanding of relevant data standards and governance.
Bachelor's, Master's, or Ph.D. in Data Science, Statistics, Biostatistics, Computer Science, or related discipline.
Ideal Candidate Profile
Strong technical contributor with hands-on experience building scalable ML and AI solutions in clinical or healthcare data contexts.
Experienced in applying AI/GenAI technologies such as LLMs, RAG frameworks, and agentic AI for clinical workflows.
Able to independently translate complex clinical data problems into structured analytical frameworks, and communicate with both technical and clinical stakeholders effectively.