Data Reporting Analyst

The Data & Reporting Analyst is a key technical role within the WISeR Model team. This individual will be responsible for building, maintaining, and evolving the data infrastructure, reporting pipelines, and analytical capabilities that power program operations across the assigned Innovaccer jurisdiction. Reporting to senior program leadership, this role sits at the intersection of healthcare data, operational performance, and regulatory compliance. The ideal candidate is a technically proficient analyst and problem-solver who is equally comfortable writing Python scripts and MongoDB queries as they are translating complex datasets into clear, actionable insights for clinical, operational, and CMS stakeholders. The analyst will play a foundational role in designing the data architecture and reporting framework that supports prior authorization review, pre-payment medical review, exemption program tracking, and provider performance monitoring. Key Responsibilities ● Design, build, and maintain scalable data pipelines that ingest, transform, and store prior authorization, pre-payment review, claims, and provider activity data from multiple sources. ● Develop and manage MongoDB collections and schemas to support the full prior authorization lifecycle: submission, review, determination, UTN assignment, resubmission, peer-to-peer review, and final determinations. ● Write Python scripts to automate ETL processes, reducing manual effort and ensuring data freshness for operational reporting. ● Establish data validation and quality control processes to identify and remediate missing, inconsistent, or erroneous data at the point of ingestion. ● Maintain documentation for all data models, pipeline logic, and schema structures to support auditability and team knowledge transfer. ● Build and maintain real-time and scheduled operational dashboards tracking key WISeR program metrics: prior authorization volumes, determination turnaround times, resubmission rates, non-affirmation rates by provider and service type, and pre-payment review rates. ● Design and automate exemption program tracking reports, including affirmation threshold calculations, qualifying provider identification, and quarterly exemption status changes. ● Build compliance monitoring reports that flag SLA breaches in near real time. ● Create executive and client-facing summary reports that distill program performance into clear, accurate, and visually effective presentations. ● Establish a consistent reporting cadence and ensure on-time delivery with full data integrity. ● Analyze prior authorization and pre-payment review data to identify trends in non-affirmation rates, documentation gaps, provider behavior patterns, and service utilization. ● Conduct root cause analyses on operational performance issues — including review delays, SLA misses, and documentation failure rates — and deliver data-backed recommendations to leadership. 1 ● Model the impact of process or policy changes on review volumes, staffing requirements, and program timelines to support capacity planning and operational decision-making. ● Analyze exemption program data to assess program effectiveness, provider compliance trends, and the impact of exemption status on overall prior authorization volumes. ● Surface data-driven insights to clinical and compliance teams to support continuous improvement in review quality and consistency. ● Ensure all data handling, storage, and reporting processes comply with HIPAA requirements, including proper handling of Protected Health Information (PHI) and Medicare Beneficiary Identifiers (MBIs). ● Implement and maintain MBI masking protocols in all data outputs and reports — replacing all MBI characters except the last four with Xs, per CMS guidelines. ● Establish role-based access controls and audit logging for data systems to support compliance and program integrity reviews. ● Maintain a complete data audit trail for all prior authorization determinations, pre-payment review outcomes, and exemption status changes to support CMS audit requirements. ● Participate in CMS and program audits by providing accurate, timely data extracts and clear documentation of data lineage and methodology. ● Partner with operations, clinical, compliance, and provider education teams to understand their data needs and build reports and tools that directly support their workflows. ● Collaborate with MAC partners on data reconciliation, claims matching, and coordinated reporting on shared program metrics. ● Translate technical data findings into clear narrative summaries and visualizations accessible to non-technical stakeholders. ● Maintain a self-service reporting environment where operational and clinical staff can access standard reports and dashboards without requiring analyst intervention for routine queries. Qualifications Required ● Bachelor's degree in Computer Science, Data Engineering, Statistics, Health Informatics, or a related quantitative field (Master's preferred). ● 5+ years of hands-on experience in data engineering, analytics engineering, or a closely related role. ● Strong proficiency in Python for ETL, scripting, and data manipulation (pandas, PyMongo, requests, etc.). ● Production experience with MongoDB — schema design, aggregation pipelines, indexing, and performance tuning. ● Proven track record building operational dashboards and executive reporting (Tableau, Power BI, Looker, Metabase, or equivalent). ● Strong SQL skills and experience working with both structured and semi-structured data. ● Demonstrated experience handling PHI under HIPAA, including masking, de-identification, and access controls. ● Excellent written and verbal communication skills, with the ability to translate technical findings for non-technical audiences.