SUMMARY:
- Develop and implement a strategic data analytics roadmap for the healthcare payer business, aligned with overall business objectives.
- Design and execute complex data analysis projects focused on areas like risk rating, claims adjudication, and enrollment optimization.
- Conduct statistical analysis and modeling to identify trends, patterns, and key insights from healthcare payer data.
- Minimum 5 years of experience in healthcare payer analytics, with a proven track record of success in leading and delivering impactful projects
- Strong understanding of risk adjustment methodologies (e.g., Hierarchical Condition Category (HCC) coding) and their impact on healthcare payer reimbursement.
- In-depth knowledge of healthcare claims and enrollment data structures and processes.
- Proven experience utilizing big data technologies like Hadoop, Spark, or similar on cloud platforms like AWS.
- Proficiency in programming languages like Scala, Python, or R for data manipulation and analysis.
- Excellent communication, presentation, and interpersonal skills with the ability to effectively translate technical findings to a non technical audience.
KEY DUTIES AND RESPONSIBILITIES:
- Design, develop, and maintain robust data pipelines using Python and PySpark to process large volumes of healthcare data efficiently in a multitenant analytics platform.
- Collaborate with crossfunctional teams to understand data requirements, implement data models, and ensure data integrity throughout the pipeline.
- Optimize data workflows for performance and scalability, considering factors such as data volume, velocity, and variety.
- Implement best practices for data ingestion, transformation, and storage in AWS services such as S3, Glue, EMR, and Redshift.
- Model data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases to support data processing requirements.
- Design and implement ETL processes using Python and PySpark to extract, transform, and load data from various sources into target databases.
- Troubleshoot and enhance existing ETLs and processing scripts to improve efficiency and reliability of data pipelines.
- Develop monitoring and alerting mechanisms to proactively identify and address data quality issues and performance bottlenecks.
Healthcare Experience:
Must have:
- 5+ years of experience in healthcare data Analytics, preferably in a health insurance payer, hospital, health system, managed care organizatio or consulting firm
- Strong understanding of healthcare terminology, regulations, and compliance requirements (e.g., HIPAA, CMS guidelines)
- Experience with healthcare quality metrics, performance measurement, and reporting methodologies
- Knowledge of healthcare reimbursement systems, revenue cycle management, and financial analysis principles
- Familiarity with healthcare information technology (IT) systems, electronic health records (EHRs), and health information exchanges (HIEs)
- Ability to communicate complex healthcare data and findings effectively to diverse stakeholders, including executives, clinicians, and non-technical staff