Prospective Payment Agreement Data Analyst

**This is a temporary position for 5 months**

Serve as a data analyst supporting the Defense Health Agency’s (DHA) centralized Federal Medical Patient Care Billing & Collection program. The PPA Data Analyst develops and sustains the annual Prospective Payment Amounts (PPAs) for Public Health Service (PHS) and National Oceanic & Atmospheric Administration (NOAA), produces quarterly analytics and reconciliations, and enables audit ready, data driven decision making across the DHA Uniform Business Office (UBO).

**This is a temporary position for 5 months**

Responsibilities:

• Collect, cleanse, and validate MEPRS, MDR, and other cost/utilization datasets required for PHS and NOAA PPAs.
• Develop standardized cost model templates, calculate annual PPAs and perform quarterly variance, trend, and sensitivity analyses.
• Design, implement, and maintain automated data pipelines feeding PPA dashboards; partner with the BI Developer/Analyst to ensure timely refresh cycles and high-quality data outputs.
• Produce recurring management reports and quarterly management review packets; summarize findings and recommendations for DHA leadership and interagency partners.
• Maintain complete calculation workpapers, data dictionaries, and assumptions to support internal controls and external audit requests.
• Collaborate with the PPA Specialist to develop policy memoranda, communication materials, and training resources; provide analytic inputs that drive effective change management execution.

Qualifications:

• Bachelor’s degree in Finance, Accounting, Data Analytics, Health Administration, or a related field; Master’s degree preferred
• 5+ years in healthcare cost accounting/reimbursement or revenue cycle analytics within federal or commercial healthcare environments.
• Expertise in Excel and working knowledge of SQL and one or more BI tools (Power BI, Tableau, or Qlik).
• Experience with MEPRS, defense health cost repositories, or large patient level cost datasets.
• Proven ability to convey complex financial or analytical models in clear, concise, and executive-ready deliverables for diverse stakeholders.

Preferred Experience:

• Exposure to MHS GENESIS/CPAM, GFEBS, MDR, and G-Invoicing data flows.
• SAS, Python, or R for data wrangling/validation; experience building data quality checks.
• Prior work with interagency reimbursable agreements and quarterly reconciliation processes.

Clearance:

• Active Public Trust