The Data Scientist will develop, validate, and operationalize advanced analytical and machine-learning models to support Health IT operations and decision-making. They will also collaborate with Data Engineers to ensure model scalability while maintaining rigorous documentation and data quality standards.
This is a remote position.
We are looking for a candidate to perform advanced statistical, analytical, predictive, and data-science work supporting Health IT operations, modernization, planning, and decision support. The Data Scientist develops, evaluates, validates, documents, and operationalizes approved analytical models and methods within authorized Government-managed environments.
Duties and Responsibilities
Perform advanced exploratory, statistical, predictive, and quantitative analyses using Government-approved data.
Develop, test, validate, and document statistical, machine-learning, predictive, forecasting, classification, or other appropriate analytical models.
Perform feature engineering, model selection, model validation, performance assessment, and analytical sensitivity testing.
Develop reproducible analytical workflows, code, model documentation, data-preparation procedures, and supporting technical artifacts.
Evaluate model quality, limitations, assumptions, bias, reliability, interpretability, and suitability for intended uses.
Develop visualizations, analytical reports, model-performance summaries, and technical findings.
Collaborate with Data Engineers to operationalize Government-approved analytical models within authorized Government-managed environments and support scalability and maintainability.
Monitor approved analytical models and methods for performance degradation, changes in underlying data, or other conditions requiring reassessment.
Support data-quality assessment, analytical validation, and testing activities.
Translate complex analytical results into clear technical and executive-level information appropriate to the intended audience.
Maintain documentation sufficient to support reproducibility, validation, governance, and applicable security and privacy requirements.
Requirements
Demonstrated advanced experience in data science, statistics, predictive analytics, machine learning, or related quantitative disciplines.
Proficiency with analytical programming languages and applicable statistical, data-science, visualization, and modeling tools.
Knowledge of model development, validation, performance assessment, data
preparation, and analytical governance.
Ability to communicate complex analytical concepts and results clearly to technical and nontechnical audiences.
Strong problem-solving, documentation, and analytical skills.
Experience with healthcare, Health IT, clinical data, or similarly complex regulated data environments is preferred.
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