Physician/Faculty Compensation Analyst

The Physician/Faculty Compensation Analyst is responsible for providing analytic support related to physician/faculty and provider compensation and productivity efforts and the related Data Repository and Reporting Solution (Solution). Under the direction of the Physician/ Faculty Compensation Leader, the analyst manages the technical elements of faculty and physician compensation, documentation, and communication; contributes to planning the initial and subsequent Solution rollout schedules; and analyzes the faculty and physician productivity and compensation plans.
DUTIES AND RESPONSIBILITIES

Data Repository and Reporting Solutions

• Implements and updates the Data Repository and Reporting Solution. Develops and applies various controls and processes to maintain the accuracy, completeness, and validity of data throughout its lifecycle.
• Collects, consolidates, and reports faculty and physician compensation and productivity data.
• Conducts extensive data mining and abstracting of faculty physician productivity data for reporting needs.
• Develops, refines, implements, and communicates enhancements to the Solution.
• Understands reporting requirements and uses of the data and ensures reports and dashboards support the development of data-driven insights.
• Designs and implements a standard process for productivity and compensation report distribution and mechanisms to support transparency.
• Continually improves the Solution design to enhance the user experience and number of useful applications (year-end communications, real time reporting, incentive calculation and communication).

Data Integrity

• Conducts validation checks, access controls, regular backups, and audits.
• Resolves data and analytic errors.
• Refines all repository data elements for all funding (including Clinical, Academic, Research, Teaching and Service - CARTS) pay and productivity elements, ensuring the accuracy of data and the integrity and stability of data sources.
• Collaborates with departments to ensure data integrity and process improvement.

Reporting

• Performs analysis, identifies results, and presents findings to support informed decision-making.
• Prepares and ensures the distribution of faculty and physician compensation and productivity reports, compensation letters, and any other associated data to leadership and providers.
• Analyzes compensation plan outcomes against plan designs and goals and calculates the impact of compensation plan changes on both compensation and productivity, and audits compensation plans outcomes.
• Develops visual models and presentations that highlight opportunities to support strategic planning and initiatives, improve performance, project future demand, and advance Medical School (UMMS) and M Physicians goals.
• Analyzes large data sets to identify trends and patterns.
• Presents actionable data to end users in appropriate formats, including reports using Microsoft Access, Word, Excel, or PowerPoint.
• Supports users in interpreting and presenting data, including presentations to individuals and groups.
• Develops, implements, and maintains various data reporting structures.
• Prepares executive reports for review by UMMS/MPhysicians leadership and the Faculty Compensation Committee.
• Develops and maintains reports for compensation survey participation.
• Conducts market research and analyzes industry-specific trends to ensure compensation models are competitive, sustainable, and aligned with corporate performance standards.
• Supports and ensures a consistent approach to the financial analysis and impact modeling required for compensation plan development, effectiveness, and sustainability.
  

QUALIFICATIONS

• Bachelor of Arts or Science in business, finance, accounting, data analytics/science, human resources, computer science, or related field
• 6 years of experience in compensation modeling, with at least 2 years experience with faculty physician compensation models
• 3 years of experience managing large databases with complex financial and data analysis
• Excellent statistical analysis, data mining, and data modeling skills.
• Knowledge of programming languages for database management.
• Ability to create clear and informative visualizations using tools like Tableau or Power BI.
• Ability to effectively communicate findings and insights to both technical and non-technical audiences.
• Ability to identify and solve problems using data analysis techniques.
• Understanding of business processes and how data can be used to drive business decisions.