Senior Quantitative Scientist, ML/LLM

Role overview A senior quantitative scientist is needed to advance machine learning and large language model applications within a healthcare real-world evidence platform. The role partners closely with data science, product, engineering, and medical teams to turn complex clinical questions into analytics and NLP solutions that unlock insights from large electronic health record datasets across several therapeutic areas. It is a hands-on position that combines research, production model work, and cross-functional mentorship.

Responsibilities - Evaluate, fine-tune, deploy, and monitor pretrained language models for healthcare use cases, with an emphasis on clinical notes - Lead research on language modeling approaches, prioritizing scientific accuracy, robustness, and explainability - Translate clinical investigation questions from commercial, product, and medical stakeholders into detailed analytics and modeling requirements - Build and refine algorithms, study plans, and analyses that support commercial real-world data products and external research collaborations - Establish best practices for data exploration, end-to-end model lifecycle management, and code, data, and documentation hygiene - Mentor and share knowledge with teammates on machine learning and natural language processing standards

Requirements - Doctorate in a quantitative field such as data science, computer science, machine learning, biostatistics, or health economics with 3+ years of relevant experience, or a Master's degree with 5+ years of experience - 5+ years of hands-on experience working with messy real-world data such as electronic health records or outcomes data - 3+ years of hands-on experience implementing and deploying machine learning models, particularly on clinical text - 3+ years of hands-on experience with transformer architectures and large language models, including generative LLMs, fine-tuning, retrieval-augmented workflows, and foundational models like BERT or RoBERTa applied to named entity recognition, text classification, and relation extraction - Strong proficiency with Python, PySpark, R, and SQL, plus platforms such as Databricks, Amazon SageMaker, and Visual Studio Code - Familiarity with clinical coding systems including ICD, CPT, and RxNorm, and ability to communicate findings clearly to mixed audiences

Nice to have - Experience working with medical imaging data

Benefits and work setup - Salary range of $141,441 to $176,801 USD, with a geographic premium that may apply to base pay - Comprehensive medical, dental, and vision insurance - 401(k) match, flexible time off, paid parental leave, and an annual learning and wellness stipend - Remote-friendly across a wide set of U.S. states, with hybrid expectations for candidates near major office hubs and priority consideration for those in the Bay Area, New York City, and Knoxville - Must be authorized to work in the U.S.; visa sponsorship is not available for this role