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Job Title: Data Scientist

Experience: 4-6 Years

Key Responsibilities:

Claims Data Analytics & Modeling

• Analyze medical, pharmacy, and hospital claims data (e.g., CPT, HCPCS, ICD-10, DRG, NPI, etc.).

• Identify fraud, waste, and abuse (FWA) patterns in claims data.

• Develop predictive models for risk stratification, readmission prediction, and cost forecasting.

• Work on value-based care models, risk adjustment, and population health analytics.

• Perform longitudinal analysis of patient journeys across different providers and payers.

Machine Learning & Advanced Analytics

• Develop and deploy ML models for claims adjudication, denial prediction, and provider benchmarking.

• Implement NLP techniques to extract insights from unstructured clinical notes.

• Utilize time-series forecasting for claims trend analysis and cost prediction.

• Optimize claims processing workflows using AI-driven automation.

Data Engineering & Management

• Work with large-scale healthcare databases

• Work with SQL, Python, R, PySpark, and cloud-based big data solutions (AWS, Azure, GCP).

Required Skills & Qualifications:

• 4-6 years of experience in healthcare data science, with a strong focus on medical claims analytics.

• Strong knowledge of US healthcare claims datasets (Medicare, Medicaid, commercial payers).

• Proficiency in SQL, Python, R, and PySpark for data analysis and modeling.

• Hands-on experience with ML frameworks (TensorFlow, Scikit-learn, XGBoost).

• Experience with healthcare standards & terminologies (ICD-10, CPT, HCPCS, NPI, DRG).

• Strong expertise in statistical modeling, predictive analytics, and NLP techniques.

• Familiarity with healthcare regulatory requirements (HIPAA, CMS guidelines, FWA detection).

• Familiarity with BI tools like Tableau, Power BI, Looker.