Position Overview
The Financial & Data Analyst will support organizational decision-making by analyzing operational, financial, and clinical data across the organization’s systems. This role is responsible for identifying trends, uncovering insights, and providing actionable recommendations that improve operational efficiency, financial performance, and data-driven decision making.
The ideal candidate combines strong analytical and financial skills with technical expertise in SQL and data analysis. This role will frequently work with large datasets from internal systems, including electronic health records (EHR), billing platforms, and operational databases to evaluate business performance and support leadership initiatives.
This role requires the ability to translate complex data into clear insights that can guide both operational and strategic decisions.
Key Responsibilities
Data Analysis & Reporting
- Analyze large datasets from operational and financial systems to identify trends, anomalies, and performance opportunities.
- Develop queries and datasets using Microsoft SQL Server (MSSQL) to extract and analyze data.
- Create and maintain dashboards, reports, and analytical models to support business leaders.
- Support development of data-driven insights related to clinical operations, revenue cycle, and organizational performance.
Financial Analysis
- Analyze financial performance across service lines, providers, and operational units.
- Identify trends related to reimbursement, billing performance, and operational costs.
- Support financial forecasting and performance analysis initiatives.
- Partner with finance and operational teams to identify opportunities for revenue improvement and cost optimization.
Business & Process Analysis
- Evaluate operational workflows and identify opportunities to improve efficiency and effectiveness.
- Investigate operational issues through data analysis and provide recommendations for improvement.
- Assist leadership teams in evaluating the impact of operational or system changes.
Data Integrity & Validation
- Validate data accuracy across systems and reporting environments.
- Identify discrepancies between operational workflows and reported data.
- Assist with development and maintenance of reporting datasets and data structures.
Cross-Functional Collaboration
- Work closely with finance, operations, clinical leadership, and technology teams to understand reporting needs.
- Translate business questions into analytical approaches and reporting solutions.
- Communicate findings clearly through presentations, dashboards, and written summaries.
Required Qualifications
- Bachelor’s degree in Finance, Data Analytics, Business Analytics, Information Systems, Healthcare Administration, or related field
- 3–5 years of experience in financial analysis, data analysis, or business analytics
- Strong experience with SQL (Microsoft SQL Server preferred)
- Experience working with large datasets and relational databases
- Strong analytical and problem-solving skills
- Ability to translate complex data into clear insights for business leaders
- Strong written and verbal communication skills
- Advanced proficiency with Microsoft Excel
Preferred Qualifications
- Experience in healthcare, healthcare technology, or revenue cycle operations
- Experience with Power BI, SSRS, or other business intelligence tools
- Knowledge of healthcare billing concepts (CPT, ICD-10, claims workflows, reimbursement models)
- Experience working with EHR or healthcare operational data
- Familiarity with financial modeling or operational performance analysis
Key Competencies
- Analytical thinking and problem solving
- Financial and operational insight
- Data storytelling and communication
- Attention to detail
- Ability to work independently and prioritize work across multiple projects
What Success Looks Like in This Role
- Deliver clear insights that help leadership understand operational and financial performance
- Identify opportunities for process improvement through data analysis
- Build reliable datasets and reports that support ongoing decision-making
- Help the organization become more data-driven in both operational and financial decisions
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