Sr. Data Scientist - Clinical AI
About The Position
Johns Hopkins Medicine is innovating a new generation of AI tools that improve clinical decision-making and reduce operational burden. As a Senior Data Scientist within the Platforms & Integrations group, you will lead the design, development, and evaluation of applied machine learning solutions that bridge research and real-world healthcare delivery. This role is ideal for a strategic thinker who wants to help shape how Johns Hopkins approaches AI-enabled transformation in medicine. General Position Summary: The Senior Data Scientist will serve as a lead contributor to applied ML initiatives at the intersection of clinical care and software development. You will collaborate with engineering teams and clinicians to identify high-impact use cases, build and evaluate in-house solutions, and guide the responsible translation of those solutions into clinical settings. You will also facilitate the evaluation of vendor AI solutions by partnering with IT teams and business stakeholders to instrument enterprise systems.
Requirements
- Master’s degree in mathematics, statistics, computer science, biomedical informatics, or related field
- 5 or more years of relevant quantitative and qualitative research and analytics experience
- proficiency in Python and SQL
Nice To Haves
- Experience building and evaluating model deployments in a regulated or sensitive environment
- Experience working with healthcare data formats (e.g. Epic Clarity & Caboodle, FHIR, OMOP)
- Experience building with model SDKs like John Snow Labs Healthcare NLP Library
- Hands-on use of cloud data and ML platforms such as Azure ML, Databricks, or Microsoft Fabric
- Familiarity with large language models prompt engineering techniques and integration into workflows
- Proficiency in Scala
- Ability to balance rigor and pragmatism in model development, including appropriate simplification for operational use
Responsibilities
- Design and implement machine learning models tailored to clinical and administrative data, including classification, risk stratification, natural language processing, and large language model prompting
- Collaborate with clinical, research, and technical teams to translate research-grade models into production-grade prototypes suitable for integration with Epic
- Lead evaluation efforts for AI/ML models, including definition of success metrics (e.g. F1, ROUGE, groundedness), comparative benchmarking, and error analysis
- Contribute to the evaluation and selection of vendor AI tools, including RFP support and benchmarking
- Apply explainability and fairness techniques to ensure models are safe, understandable, and equitable in high-stakes environments
- Contribute to the development of a repeatable approach for AI solution pilots and rollouts, including evaluation gates, stakeholder education, and feedback mechanisms
- Communicate findings to diverse audiences including clinicians, IT leaders, and informaticists in clear and accessible terms
- Contribute to publications when projects support dissemination
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
