• Supervise and develop a team of data analysts, creating goals and career growth opportunities • Build and lead a guild of analysts to mature processes and techniques that overcome common challenges • Foster a culture of continuous improvement, analytical excellence, and rigorous validation • Establish practices for proving that solutions work before full deployment • Build strong relationships with stakeholders across business areas, spending routine time understanding their needs • Lead structured discovery conversations that translate ambiguous requirements into well-defined, actionable work • Guide stakeholders through a disciplined process to identify work that delivers measurable business value • Work with the Data Platform Manager to coordinate team priorities and deliver maximum value • Bridge the gap between technical and non-technical audiences through clear communication • Conduct comprehensive data profiling to deeply understand what the data means, including its quality, patterns, and business context • Design data models that serve critical business needs, from profiling source data to prototyping dimensional models • Collaborate with Data Warehouse Engineers to refine models and develop transforms to populate them • Validate and test analytical solutions to prove they work before broader implementation • Create compelling reports and dashboards in Power BI that measure what truly matters • Define and classify key metrics that drive business decisions • Develop data governance frameworks, including data dictionaries, data mapping, and automated profiling • Document data meaning and lineage to build organizational knowledge • Increase stakeholder ability to use and author their own reports, working toward self-service analytics • Serve as a subject matter expert, deepening the organization's understanding of business processes and data needs • Monitor usage and adoption to continuously improve data products

• In collaboration with the data analytics team and under the direction of the Chief Member Experience Officer, the Data Analyst will create dynamic, interactive and intuitive business intelligence reports, dashboards and visualizations to support business decisions, and assure the accuracy and integrity of data. • This position can be remote.

About Us: Our purpose is to help clients exceed their financial health goals. Across the reimbursement cycle, our scalable solutions and clinical expertise help solve programmatic needs. Enabling our teams with leading technology allows analytics to guide our solutions and keeps us accountable achieving goals. We build long-term careers by investing in YOU. We seek to create an environment that cultivates your professional development and personal growth, as we believe your success is our success. JOB SUMMARY: The WISeR Data Analyst plays a critical role in transforming operational, clinical, and system data into actionable insights that drive productivity, quality, compliance, and scalability of the WISeR program. This position serves as a strategic partner to operations leadership, clinical reviewers, training teams, and external stakeholders by delivering accurate, timely, and meaningful analytics. The analyst is responsible for end-to-end data ownership—from data ingestion and validation to reporting, interpretation, and executive level storytelling. This role supports both day-to-day operational decisions and long-term strategic initiatives, including staffing models, productivity optimization, quality improvement, AI performance monitoring, and payer related escalations. ESSENTIAL DUTIES AND RESPONSIBILITIES: Note: The essential duties and responsibilities below are intended to describe the general duties and responsibilities of this position and are not intended to be an exhaustive statement of duties. This position may perform all or most of the primary duties listed below. Specific tasks, responsibilities or competencies may be documented in the Team Member’s performance objectives as outlined by the Team Member’s immediate Leadership Team Member. Core Responsibilities 1. Operational & Productivity Analytics - Monitor daily, weekly, and monthly WISeR productivity metrics, including: - Case volumes - Turnaround time (TAT) - Affirmation vs. non‑affirmation rates - Backlog levels and aging - Rework and appeal frequency - Identify trends, outliers, and performance gaps at individual, team, and program levels. - Support staffing and scheduling decisions through workload modeling and capacity analysis. - Provide real‑time and retrospective insights to leadership to support rapid decision‑making. 2. Reporting, Dashboards & Visualization - Design, develop, and maintain dashboards and standardized reports for: - Executive leadership - Operations and training teams - Clinical leadership - Translate complex data into clear, concise visuals and narratives. - Ensure reporting accuracy, consistency, and alignment with defined KPIs. - Automate recurring reports where possible to improve efficiency and reliability. 3. Quality, Accuracy & Compliance Analytics - Analyze documentation trends impacting quality, including: - Missing or inconsistent pain scales - Fluoroscopy documentation gaps - Incomplete medical necessity support - Track error patterns leading to non‑affirmations, appeals, and rework. - Support internal audits and compliance monitoring with data validation and reporting. - Assist in identifying systemic risks related to CMS, Medicare, PECOS, and UTN workflows. 4. AI & Technology Performance Monitoring - Monitor AI‑assisted workflow performance and adoption trends. - Analyze AI accuracy, override rates, and downstream operational impact. - Partner with training and technical teams to surface AI improvement opportunities. - Support technology optimization initiatives through data‑driven insights. 5. Stakeholder Partnership & Communication - Act as a data liaison between analytics and non‑technical stakeholders. - Present findings and recommendations to leadership with confidence and clarity. - Support payer, vendor, and partner discussions with data‑backed insights. - Collaborate cross‑functionally with operations, clinical, IT, compliance, and training teams. 6. Process Improvement & Data Governance - Identify opportunities to streamline workflows and reduce manual effort through analytics. - Support continuous improvement initiatives using Lean or performance‑based methodologies. - Define and maintain data dictionaries, metric definitions, and reporting standards. - Ensure data integrity, version control, and documentation best practices. Technical & Analytical Skills Required - Advanced Excel skills (pivot tables, advanced formulas, lookups, conditional logic). - Strong data validation and reconciliation skills. - Experience working with healthcare or operational datasets. - Ability to synthesize large datasets into meaningful insights. Preferred - Business Intelligence tools: Power BI, Tableau, or similar. - SQL or database querying experience. - Familiarity with healthcare systems, utilization management, or revenue cycle workflows. - Experience with CMS, Medicare, PECOS, UTN, or prior authorization processes. - Exposure to AI‑enabled workflows or automation platforms. Education & Experience Required - Bachelor’s degree in Data Analytics, Healthcare Administration, Business, Information Systems, or related field (or equivalent experience). - 2–4 years of experience in data analysis, reporting, or operational analytics. Preferred - Healthcare analytics experience. - Experience supporting clinical or physician‑driven workflows. - Experience in fast‑paced, metrics‑driven environments. Key Competencies - Analytical thinking and problem‑solving - Data accuracy and attention to detail - Executive‑level communication and data storytelling - Cross‑functional collaboration - Confidentiality and compliance awareness - Continuous improvement mindset PHYSICAL DEMANDS: Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions as described. Regular eye-hand coordination and manual dexterity is required to operate office equipment. The ability to perform work at a computer terminal for 6-8 hours a day and function in an environment with constant interruptions is required. At times, Team Members are subject to sitting for prolonged periods. Infrequently, Team Member must be able to lift and move material weighing up to 20 lbs. Team Member may experience elevated levels of stress during periods of increased activity and with work entailing multiple deadlines. A job description is only intended as a guideline and is only part of the Team Member’s function. The company has reviewed this job description to ensure that the essential functions and basic duties have been included. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate.

• Drive analytics discussions with leadership and cross functional teams to build consensus on business and technical definitions of KPI/metrics. • Create reliable and efficient queries transforming and extracting large data sets for dashboarding and data visualization. • Build expertise in metric definitions and calculations to ensure accurate and proper interpretation of core business metrics and drivers. • Partner with the cross functional teams to drive projects and processes that contribute to improvements in data integrity. • Manage a small team of analytics engineers/analysts. • Identify opportunities to optimize reporting processes, data integration, and automation and partner with the broader team to execute on enhancements. • Use data visualization and analytic tools to grasp business insights, and to create consumable data visualizations and recommendations that influence business outcomes. • Analyze key performance metrics to identify root cause of performance issues. • Regularly communicate performance trends and improvements to senior management and leadership ensuring they can talk to service-specific performance. • Ensure all programs have clear, quantifiable outcomes and measures that drive improved performance. • Build and manage analytics pipeline processes using dbt or similar tools.