Machine Learning Healthcare Data Scientist
Indexed description
Responsibilities Include:
- Create Machine Learning models in support of a behavioral health data analytics team
- Leverage Python/R for data analysis
- Apply clustering, regression, NLP, predictive modeling to create informative Machine Learning models
- Collaborate cross-functionally with public health teams, clinicians, and leadership to translate data into actionable strategies for quality improvement
- Conduct audits, data validation, and performance analyses to ensure data quality, regulatory compliance, and accurate reporting
- Contribute to AI/ML-enabled digital health solutions, including mental health risk classifiers and wellness monitoring tools
- Possess exceptional business acumen and outstanding communication to present findings and visualizations to executives and technical/ non-technical stakeholders
- Bachelor’s degree required (data science, statistics, public health, healthcare analytics, or related field).
- 1-3+ years of experience with statistical analysis and predictive analytics using Python or R
- Experience with Machine Learning model development for healthcare quality and population health analytics
- Experience with predictive modeling techniques including classification, regression, risk scoring, and stratification
- Experience with ML libraries/frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar
- Experience working with large, structured healthcare datasets
- Experience with healthcare data analysis: claims, encounter, EHR, member and provider datasets
- Ability to analyze healthcare quality metrics (HEDIS, CMS, NCQA, preferred)
- Knowledge of population health analytics and member risk segmentation
- Experience with data preprocessing, feature engineering, and model validation, preferred
- Experience with SQL querying and relational database analysis, preferred
- Experience with data visualization and reporting using Power BI, Tableau, or similar BI tools, highly preferred
- Knowledge of healthcare interoperability and coding standards (ICD-10, CPT, HCPCS, SNOMED, LOINC)
- Understanding of healthcare utilization, care management, and quality improvement initiatives
- Familiarity with CMS, NCQA, and HEDIS reporting methodologies
- Model performance evaluation using precision/recall, ROC-AUC, confusion matrices, and cross-validation
- Experience developing dashboards, KPIs, and analytical reporting for healthcare stakeholders
- Exposure to cloud analytics (AWS, Azure, or GCP) preferred
- Hanover, MD- HYBRID (1 day a week in office, required)
AVER is an Equal Opportunity Employer/Veterans/Disabled
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