NLP / LLM Data Scientist

Role overview Build and run natural language processing and large language model pipelines that turn complex clinical data into AI-ready datasets for external developers, pharma, and medical-device teams. The role sits inside a data science team that owns the creation and maintenance of high-quality, HIPAA-compliant datasets drawn from real-world multimodal healthcare sources, reporting to the Data Science Manager.

Responsibilities - Develop NLP, LLM, and other ML-based pipelines to abstract relevant labels from text-based healthcare data and store them in scalable data models. - Query complex health data sources, including EMRs, semi-structured reports, and free-text clinical notes, to identify key elements and curate high-quality datasets for real-world evidence and AI training. - Own data extraction, wrangling, labeling, and QC for analytical datasets that include abstracted clinical concepts. - Stay current on applied NLP and generative AI methods and integrate them where they add value. - Support design, testing, validation, analysis, and merging of multimodal data structures spanning tabular records, images, video, and waveforms. - Deliver well-documented, HIPAA-compliant data products on time and explain abstraction methods and findings to audiences with mixed technical and clinical backgrounds.

Requirements - Advanced degree in a quantitative field such as data science, biomedical informatics, computer science, or biostatistics, or a BS with at least five years of relevant professional experience. - At least two years of data science and machine learning experience building pipelines that extract and curate unstructured and semi-structured data using advanced ML and AI techniques; clinical or healthcare data experience is a strong bonus. - Fluency in Python and SQL, including ML and NLP libraries such as PyTorch, TensorFlow, and HuggingFace. - Familiarity with modern applied LLM techniques on real-world data. - Strong technical writing, editing, and communication skills, plus solid organizational habits and the ability to manage multiple projects against deadlines.

Nice to have - Experience with electronic medical record systems such as Epic, Cerner, or Allscripts; medical ontologies; DICOM or other imaging modalities; AWS; Git; encryption methods; peer-reviewed publications; or prior startup experience.

Benefits and work setup - Remote work with flexible hours and occasional in-person company working days roughly each quarter. - Wellness benefits including healthcare, dental, vision, PTO, sick days, and professional development days, with an academic culture balanced against startup speed and flexibility.