Senior Data Scientist

About the role

The Senior Data Scientist I investigates and resolves complex healthcare data issues across client implementations, regulatory reporting, operational processes, and data integration workflows. This role analyzes healthcare data, SQL code, ETL processes, technical specifications, and business rules to identify root causes, validate processing results, and recommend solutions that support data accuracy, client deliverables, operational processes, and encounter submission capabilities. The Senior Data Scientist I collaborates with technical, operational, client service, and business teams, documents findings and recommendations, and communicates analytical results to technical and non-technical audiences.

Responsibilities

• Healthcare Data Analysis
  • Investigates and resolves complex healthcare data issues, discrepancies, and operational questions.
  • Performs root-cause analysis by reviewing source data, SQL code, ETL processes, business rules, and processing workflows.
  • Analyzes claims, encounter, enrollment, eligibility, provider, and financial data to identify trends and data issues that affect client deliverables and operational processes.
• Data Quality and Technical Review
  • Writes and maintains complex SQL queries for data validation, analysis, troubleshooting, reconciliation, and reporting.
  • Reviews data transformations, ETL processes, technical specifications, and business rules to identify data quality and processing issues.
  • Validates processing results and recommends corrective actions to improve data accuracy and reporting.
• Collaboration and Solution Development
  • Collaborates with developers, analysts, operations teams, client service teams, and business stakeholders to define problems, evaluate impacts, and implement solutions.
  • Translates analytical findings into recommendations that support data integration, reporting, operational processes, and encounter submission capabilities.
  • Serves as a subject matter resource for assigned clients, data domains, business rules, and processing methodologies.
• Documentation and Communication
  • Documents findings, recommendations, data issues, business rules