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Strong employer brand and metro location but niche LLM/clinical specialization reduces generic applicant density.
Role requires clinical-trial, patient-data, and healthcare domain expertise, limiting cross-industry transferability.
PhD, 2+ years, LLM tooling and clinical trial domain expertise are explicit mandatory filters.
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Develop and implement Generative AI and ML solutions to automate and optimize clinical trial operations such as enrollment forecasting, cost optimization, and site selection.
Fine-tune large language models for clinical trial analytics including protocol comparison, trial similarity, data harmonization, and eligibility criteria evaluation.
Create patient modeling and enrollment simulation tools to provide accurate projections for clinical trial enrollment completion.
Ph.D. in quantitative discipline (e.g., computer science, statistics, biostatistics, health economics, biomedical informatics, epidemiology, applied mathematics).
Minimum 2 years industry experience in Data Science with predictive technologies, forecasting, optimization, NLP, AI, or ML.
Hands-on experience with large language model application frameworks and clinical/medical LLM fine-tuning (e.g., DSPy, LangChain).
Proficiency in Python and SQL programming languages.
Experience with clinical trial operations and healthcare data domains such as real-world data (EHR, claims, registry), patient cohort building, or trial analytics.
Able to communicate complex technical methods and results clearly to diverse stakeholders to support decision-making.
Familiarity with MLOps practices and tools preferred; experience collaborating with healthcare professionals.