Revenue Cycle Data Analyst

Job Title – Position Description: Revenue Cycle Data Analyst

Reports to: VP, Revenue Cycle

Direct Reports: None — individual contributor role

Matrix Relationships: Dotted-line collaboration with other members of the Rev Cycle & Finance teams

MISSION

The Revenue Cycle Data Analyst is responsible for building and maintaining the reporting, dashboards, and data models that support the entire revenue cycle. This is a technical, individual-contributor role: the Analyst works under the direction of the VP, Revenue Cycle and partners informally with other revenue cycle and finance team members in a matrixed capacity.

We are looking for someone earlier in their career who brings strong, modern data-analytics skills, including comfort with AI/ML-assisted tools, RPA bots, databases, data visualization tools, etc. Healthcare and managed-care context is a plus but not necessary as it will be built on the job.

OUTCOMES

• Build and maintain recurring and ad hoc reports, dashboards, and data models (e.g., Excel, Power BI, SQL) that track claims volume, expected revenue, collections, denials, underpayments, and payer performance for the revenue cycle team.
• Apply modern data tools and techniques — including SQL and AI/ML-assisted analysis (e.g., using AI tools to accelerate data cleaning, pattern detection, forecasting, or documentation) — to turn large, messy claims and payment datasets into clear, actionable insight.
• Support identification of payment variances (underpayments, denials, and deviations from expected reimbursement) by comparing actual payments to contracted and government payor rates, and help quantify trends for review by the VP, Revenue Cycle and other senior team members.
• Partner informally with other members of the Revenue Cycle, Finance, and Operations teams to gather requirements, validate findings, and translate technical output into terms non-technical stakeholders can act on.
• Continuously look for opportunities to automate manual reporting processes, streamline data pipelines, and evaluate new analytics tools and AI/ML-enabled tactics as they emerge.
• Maintain clean data, clear documentation, and version control for revenue pricers, reporting tools and models so they remain reliable, well-understood, and easy for others to use or build on.
• Present findings clearly and concisely, adjusting the level of technical detail for the audience, from peer analysts to the VP, Revenue Cycle.

COMPETENCIES

Job Related Competencies:

• Manages Complexity: Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.
• Drive Results: Consistently achieving results, even under tough circumstances.
• Financial Acumen: Interpreting and applying understanding of key financial indicators to make better business decisions.
• Tech Savvy: Anticipating and adopting innovation in business building digital and technology applications.
• Business Insight: Applying knowledge of business and the marketplace to advance the organization’s goals.

Cultural Competencies

Advanced Values:

People

Collaborates: Building partnerships and working collaboratively with others to meet shared objectives

Heart

Patient Focus: Building strong patient relationships and delivering patient-centric solutions

Service

Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity

Excellence

Cultivates Innovation: Creating new and better ways for the organization to be successful

Behaviors:

Being Resilient

Rebounding from setback and adversity when facing difficult situations

Self-Development

Actively seeking new ways to grow and be challenged using both formal and informal development opportunities

Optimizes Work Processes

Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement

Professional Communication

Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences, while maintaining a professional appearance and tone

QUALIFICATIONS

Basic Qualifications

Education:

Bachelor's Degree in Data Analytics, Data Science, Computer Science, Statistics, Business Analytics, or a related field

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Work Experience:

2 – 5 years of experience in data analytics, reporting, or business intelligence (relevant internships, academic projects, or certifications will be considered alongside formal work experience)

Proficient in Microsoft Excel, with working knowledge of SQL and at least one modern data visualization tool (e.g., Power BI, Tableau)

Demonstrated interest in or hands-on exposure to AI/ML-assisted analytics tools and techniques (e.g., AI coding copilots, generative-AI-assisted data cleaning or documentation, basic predictive modeling)

No prior healthcare or managed-care experience required — willingness and aptitude to learn the industry is essential

Preferred Qualifications:

Education:

Coursework, certification, or self-directed learning in AI/ML, data science, or applied statistics

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Work Experience:

Experience using AI/ML tools in a professional or academic analytics setting (e.g., building simple predictive models, using generative AI to accelerate analysis, QA, or documentation)

Exposure to healthcare, insurance, or another data-intensive, regulated industry is a plus but not required