Note: The job is a remote job and is open to candidates in USA. SmartLight Analytics is focused on improving cost efficiency and care quality in healthcare through advanced analytics. They are seeking a Healthcare Statistical Data Scientist to design, build, and deploy machine learning models that transform healthcare claims data into actionable insights.
Responsibilities
- Develop, train, and deploy ML models for use cases such as:
- Claims cost prediction and utilization forecasting
- Fraud, waste, and abuse detection
- Risk adjustment and member stratification
- Provider performance and network optimization
- Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling
- Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value
- Build scalable pipelines for feature engineering, model training, validation, and monitoring
- Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD‑10, DRG, NDC)
- Translate domain knowledge into meaningful features and model strategies
- Partner with clinicians, product managers, and business stakeholders to define problems and measure outcomes
- Communicate complex analytical findings in clear, actionable terms
Skills
- Strong proficiency in Python and ML libraries (scikit‑learn, XGBoost, TensorFlow/PyTorch)
- Hands‑on experience with healthcare claims datasets and coding systems
- Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques
- Strong knowledge and expertise working with SQL
- Ability to translate business needs into analytical solutions
- Must have demonstrated the ability to solve complex problems with minimal direction
- Experience with NLP applied to clinical notes or unstructured healthcare data
- Familiarity with actuarial concepts, risk scoring, or value‑based care models
- Familiarity deploying models into production (MLOps, CI/CD)
- Background in health economics, epidemiology, or biostatistics
- Prior work with FHIR, HL7, or interoperability standards
Company Overview
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