Payer Analytics Specialist

Job Title: Payer Analytics Specialist 

Position Summary 

The Payer Analytics Specialist is responsible for driving insights and supporting decision-making by analyzing healthcare payer data, creating data pipelines, and managing complex analytics projects. This role involves collaborating with cross-functional teams (Operations, Product, IT, and external partners) to ensure robust data integration, reporting, and advanced analytics capabilities. The ideal candidate will have strong technical skills, payer domain expertise, and the ability to manage 3rd-party data sources effectively. 

Key Responsibilities 

1. Data Integration and ETL Pipelines 

• Develop, maintain, and optimize end-to-end data pipelines, including ingestion, transformation, and loading of internal and external data sources. 

• Collaborate with IT and Data Engineering teams to design scalable, secure, and high-performing data workflows. 

• Implement best practices in data governance, version control, data security, and documentation. 

2. Analytics and Reporting 

• Data Analysis: Analyze CPT-level data to identify trends, patterns, and insights relevant to healthcare services and payer rates. 

• Benchmarking: Compare and benchmark rates provided by different health insurance payers within designated zip codes to assess competitive positioning. 

• Build and maintain analytical models for cost, quality, and utilization metrics, leveraging tools such as Python, R, or SQL-based BI tools. 

• Develop dashboards and reports to communicate findings to stakeholders across the organization. 

3. 3rd-Party Data Management 

• Ingest and preprocess multiple 3rd party data from multiple sources and transform it into unified structures for analytics and reporting 

• Ensure compliance with transparency requirements and enable downstream analytics. 

• Design automated workflows to update and validate data, working closely with external vendors and technical teams. 

• Establish best practices for data quality checks (e.g., encounter completeness, claim-level validations) and troubleshooting. 

4. Project Management and Stakeholder Collaboration 

• Manage analytics project lifecycles: requirement gathering, project scoping, resource planning, timeline monitoring, and delivery. 

• Partner with key stakeholders (Finance, Operations, Population Health) to define KPIs, data needs, and reporting frameworks. 

• Communicate technical concepts and results to non-technical audiences, providing clear insights and recommendations. 

5. Quality Assurance and Compliance 

• Ensure data quality by implementing validation checks, audits, and anomaly detection frameworks. 

• Maintain compliance with HIPAA, HITECH, and other relevant healthcare regulations and data privacy requirements. 

• Participate in internal and external audits of data processes. 

6. Continuous Improvement and Thought Leadership 

• Stay current with industry trends, analytics tools, and regulatory changes affecting payer analytics. 

• Identify opportunities to enhance existing data processes, adopt new technologies, and promote data-driven culture within the organization. 

• Mentor junior analysts and share best practices in data analytics, reporting, and pipeline development. 

Required Qualifications 

1. Education & Experience 

• Bachelor’s degree in Health Informatics, Data Science, Computer Science, Statistics, or a related field (Master’s degree a plus). 

• 3-5+ years of experience in healthcare analytics, payer operations, or related fields. 

2. Technical Skills 

• Data Integration & ETL: Proficiency in building data pipelines using tools like SQL, Python, R, or ETL platforms (e.g., Talend, Airflow, or Data Factory). 

• Databases & Cloud: Experience working with relational databases (SQL Server, PostgreSQL) and cloud environments (AWS, Azure, GCP). 

• BI & Visualization: Familiarity with BI tools (Tableau, Power BI, Looker) for dashboard creation and data storytelling. 

• MRF, All Claims, & Definitive Healthcare Data: Hands-on experience (or strong familiarity) with healthcare transparency data sets, claims data ingestion strategies, and provider/facility-level data from 3rd-party sources like Definitive Healthcare. 

3. Healthcare Domain Expertise 

• Strong understanding of claims data structures (UB-04, CMS-1500), coding systems (ICD, CPT, HCPCS), and payer processes. 

• Knowledge of healthcare regulations (HIPAA, HITECH, transparency rules) and how they impact data sharing and management. 

4. Analytical & Problem-Solving Skills 

• Proven ability to synthesize large datasets, pinpoint issues, and recommend data-driven solutions. 

• Comfort with statistical analysis and predictive modeling using Python or R. 

5. Soft Skills 

• Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders. 

• Strong project management and organizational skills, with the ability to handle multiple tasks and meet deadlines. 

• Collaborative mindset and willingness to work cross-functionally to achieve shared objectives. 

Preferred/Additional Qualifications 

• Advanced degree (MBA, MPH, MS in Analytics, or similar). 

• Experience with healthcare cost transparency regulations and handling MRF data specifically for compliance. 

• Familiarity with Data Ops or DevOps practices to automate and streamline data pipelines. 

• Certification in BI or data engineering (e.g., Microsoft Certified: Azure Data Engineer, AWS Data Analytics Specialty). 

• Experience establishing data stewardship programs and leading data governance initiatives. 

Why Join Us? 

• Impactful Work – Play a key role in leveraging payer data to reduce costs, improve quality, and shape population health strategies. 

• Innovation – Collaborate on advanced analytics projects using state-of-the-art tools and platforms. 

• Growth Opportunity – Be part of an expanding analytics team where you can lead initiatives, mentor others, and deepen your healthcare data expertise. 

• Supportive Culture – Work in an environment that values open communication, knowledge sharing, and continuous learning.