D. degree in a quantitative discipline (e.g., computer science, statistics, biostatistics, health economics, biomedical informatics, epidemiology, applied mathematics, or similar), 2+ years of industry experience delivering on Data Science projects using predictive technologies, forecasting, multi-objective optimization, natural language processing, artificial intelligence, or machine learning, Hand-on experience with LLM application framework and tools (e.g., DSPy, LangChain) clinical/medical LLMs and finetuning techniques, Proficiency with programming languages Python and SQL, Passionate about leveraging data to drive scientific innovation, Excellent interpersonal, communication, and presentation skills. Preferred qualifications: Familiarity with MLOps practices and tools, Demonstrated experience in one of the following domains: real-world data (EHR, insurance claims, registry data), building patient cohorts, enrollment modeling, clinical trial analytics, Experience working with healthcare professionals, Ability to effectively communicate technical work to a wide audience.