Associate Data Analyst
New
N
Nomi HealthHealthcare Financial Services
RemoteFull-TimeEntry
Salary not disclosed
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Job Details
- Experience
- 0-2 years
- Required Skills
- PythonSQLMicrosoft Power BITableauR
Requirements
- 0-2 years of experience in healthcare claims analysis, payer analytics, or related field; internship or academic project experience welcome.
- Basic familiarity with Medicare and commercial payer reimbursement concepts.
- Willingness to learn reimbursement methodologies on the job.
- Working knowledge of SQL for data querying.
- Familiarity with Python or R is a plus.
- Exposure to medical and pharmacy claims data or healthcare financial concepts is a plus.
- Experience or interest leveraging AI tools to automate workflows.
- Any exposure to contract negotiations, network management, or provider relations is a plus.
- Strong communication skills and the ability to clearly present data findings to teammates and stakeholders.
Responsibilities
- Assist in analyzing medical and pharmacy claims data to identify trends, cost drivers, and opportunities for optimization.
- Support provider contracting and payer teams by pulling and summarizing data on reimbursement models, pricing structures, and fee schedules.
- Assist in building and maintaining financial models to assess payer performance, reimbursement strategies, and cost containment opportunities.
- Collaborate with sales and contracting teams to deliver ad hoc data pulls and reports that support growth initiatives.
- Work with Medicare, Medicaid, and commercial claims data to support tracking reimbursement trends and regulatory changes.
- Build and maintain reports and dashboards using SQL, Power BI, or Tableau to visualize key business metrics.
- Support evaluation of the financial impact of alternative payment models, value-based care initiatives, and provider incentives.
- Perform quality checks to ensure data integrity and accuracy in claims analysis.
- Partner with internal teams to support claims processing workflows, payment accuracy, and operational efficiencies.
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