
Senior Data Scientist
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Job overview
The Senior Data Scientist will build and deploy advanced AI and machine-learning solutions for healthcare, with applications in clinical care, operations, and patient outcomes. The role calls for deep technical experience in distributed computing, machine learning, and statistics, along with professional experience applying modeling to complex datasets. Healthcare data experience is highly valued, while several healthcare-specific tools and domains are preferred but not required.
Skills & qualifications
Skills
Qualifications
Full job description
You will work at the intersection of healthcare and AI, building and deploying advanced AI/ML solutions that transform clinical care, operations, and patient outcomes at scale. * Atlanta * Boston * Chicago * Dallas * New York City * Washington DCApply NowApply Later YOUR QUALIFICATIONS AND SKILLS * Bachelor's, Master's, or PhD in computer science, machine learning, applied statistics, mathematics, biomedical informatics, or a related quantitative field * 5+ years of deep technical experience in distributed computing, machine learning and statistics related work * 2+ years of professional experience applying machine learning and statistical modeling to complex, real-world datasets; healthcare or clinical data experience is highly valued * Strong programming skills in Python (NumPy, pandas, scikit-learn, PyTorch/TensorFlow) and SQL; experience with PySpark or another big-data framework is a plus * Experience with NLP or generative AI; including model development, fine-tuning, RAG pipeline design, or production deployment of LLM-based applications; is highly desirable * Demonstrated ability to prototype statistical and ML algorithms and apply them to new problem domains with limited supervision * Exceptional time management and the ability to manage multiple work streams in a fast-paced, largely autonomous environment * Direct experience working with clinical or healthcare data; EHR (Epic, Cerner), claims, clinical notes, ADT feeds, or device/wearables data is preferred but not required * Knowledge of healthcare data standards and interoperability frameworks (HL7, FHIR, ICD-10, SNOMED, OMOP CDM) is preferred but not required * Experience deploying AI in regulated healthcare environments, including HIPAA-compliant data handling and model governance is preferred but not required * Familiarity with healthcare operations domains: revenue cycle management (RCM), care management, clinical throughput, access optimization, population health is preferred but not required * Strong communication skills; able to explain complex model behavior, trade-offs, and clinical implications to both technical teams and non-technical healthcare leaders Apply NowApply Later Share This JobEqual Opportunity Employment Disclaimer McKinsey & Company is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other protected characteristics.
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