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Tier-1 brand, mid-level ML role and popular Data Scientist title drive high applicant competition.
Role requires biopharma clinical trial and regulated-data expertise, making cross-industry transferability limited.
Explicit 5+ years plus clinical, ML/GenAI, MLOps, and regulated-data experience creates strict screening filters.
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Design, develop, and deploy predictive modeling and AI/ML solutions including statistical analyses and AI/GenAI frameworks to support clinical development challenges.
Collaborate with clinical and operational stakeholders to translate complex datasets into actionable insights and communicate findings effectively.
Build and maintain data pipelines and apply MLOps best practices to ensure reliability and scalability of models within cloud and big data environments.
5+ years progressive experience in data science or ML engineering with exposure to biopharma, pharma, or clinical research.
Bachelor's, Master's, or Ph.D. in Data Science, Statistics, Biostatistics, Computer Science, or related discipline.
Proficiency in Python, PySpark, or R, including clinical/statistical packages and ML frameworks.
Experience working with clinical trial data, EHR/EMR, real-world evidence/data, and knowledge of clinical trial data standards.
Strong individual contributor comfortable solving moderately complex to complex problems with scientific rigor and independence.
Experience implementing AI/GenAI technologies such as LLMs, RAG frameworks, Agentic AI, and prompt engineering applied to clinical workflows.
Hands-on experience with MLOps, big data platforms (Spark), and collaborative engineering practices in regulated environments.