Healthcare Data Analyst, Methodology at PurpleLab in Remote

Summary: PurpleLab is seeking a technically strong and intellectually curious Healthcare Data Analyst to join their Data Methodology team. The role involves working with healthcare claims data to develop and validate analytical methodologies, collaborating with senior analysts and engineers, and communicating findings to diverse audiences. Responsibilities: - Work with large-scale healthcare claims datasets including closed claims, open claims, and remittance data to support the development and validation of analytical methodologies - Write and maintain complex SQL queries to support methodology development, data validation, QA, and ad hoc analyses - Assist in validating analytical outputs against expected clinical and business benchmarks to ensure accuracy and relevance - Support the development and documentation of analytical rules and calculations related to utilization, cost, quality, and clinical outcomes - Investigate data anomalies and unexpected results, escalating findings with clear documentation and reproducible analysis - Contribute to data quality frameworks and QC checklists that ensure consistency and integrity across analytical outputs - Partner with senior analysts, product managers, and engineers to understand business and clinical requirements and translate them into analytical tasks - Support product enhancements and new feature development by evaluating the feasibility and impact of methodology changes - Document methodology logic, assumptions, data definitions, and known limitations to support knowledge-sharing across teams - Help troubleshoot data and methodology issues that arise across upstream and downstream systems - Communicate analytical findings clearly through written summaries and presentations, tailoring the message for both technical and non-technical audiences - Apply working knowledge of healthcare claims coding and billing standards, including CPT/HCPCS, ICD-10-CM/PCS, and MS-DRG, in day-to-day analytical work - Adhere to HIPAA requirements and best practices for handling de-identified patient-level data - Build familiarity with clinical groupers and advanced claims methodologies (e.g., risk adjustment, episode groupers, severity stratification) through hands-on project work and mentorship - Stay current on relevant coding changes, regulatory updates, and industry trends that may affect analytical outputs Required Qualifications: - 1–3 years of professional experience in healthcare analytics, data analysis, or a closely related field - Solid SQL proficiency (required), including experience writing joins, subqueries, aggregations, and CTEs; exposure to window functions is a plus - Direct, hands-on experience working with healthcare claims data (medical, pharmacy, or both) - Working knowledge of healthcare coding and billing concepts, including CPT/HCPCS and ICD-10; MS-DRG familiarity is a plus - Demonstrated ability to analyze complex data, identify patterns, and communicate findings clearly to both technical and non-technical audiences - Strong attention to detail and a methodical approach to QA and data validation - Working knowledge of HIPAA and healthcare data privacy standards - Comfort working in a collaborative, cross-functional environment with both technical and business stakeholders Preferred Qualifications: - Exposure to advanced healthcare analytics concepts such as episode-based analytics, risk adjustment models, or population health methodologies - Hands-on experience with clinical data (e.g., EMR, Lab results, imaging) - Experience with modern data warehousing and analytics platforms (e.g., BigQuery, Databricks, Snowflake) - Familiarity with healthcare analytics products, platforms, or SaaS environments - Experience writing or maintaining technical documentation, data dictionaries, or methodology specifications - Background in healthcare economics, clinical analytics, or population health, or relevant field Required Skills: SQL, Healthcare claims data, Healthcare coding, billing, CPT/HCPCS, ICD-10, MS-DRG, Data analysis, Data validation, HIPAA compliance