Location: Lake Success, NY
Cap-Exempt H-1B Position — No lottery required
Job Description This position will support computational oncology and cancer informatics research initiatives focused on transforming complex clinical data into structured, actionable datasets for research, quality improvement, clinical trial identification, and care delivery optimization. The role will emphasize applied machine learning, natural language processing, and large language model-driven workflows using real-world clinical data, including electronic health record data, pathology reports, radiology reports, clinical notes, genomics, treatment data, and other institutional data sources. The Data Scientist will work semi-independently in close collaboration with clinical investigators, informatics teams, biostatisticians, and other data science stakeholders to design, build, evaluate, and refine computational pipelines. The ideal candidate will have practical prior experience developing data science workflows in Python and using modern machine learning or LLM-based tools in real projects. Job Responsibility - Develop, test, and maintain Python-based data pipelines for clinical research, quality improvement, and computational oncology projects. - Support cancer informatics projects involving natural language processing, machine learning, large language models, and structured extraction from unstructured clinical data. - Build workflows for processing clinical notes, pathology reports, radiology reports, treatment records, genomics reports, and other real-world healthcare data sources. - Implement and evaluate LLM-assisted workflows, including prompt engineering, structured output generation, model benchmarking, validation pipelines, and error analysis. - Assist with the development of retrieval-augmented generation workflows, vector search, embedding-based retrieval, and related approaches where appropriate. - Work with clinical subject matter experts to translate oncology-focused research questions into executable data science tasks. - Perform data cleaning,