****Strong Excel (formulas, pivot tables, lookups; basic automation/macros a plus).*******

THERE WILL BE A TEST

About the Role Data Analyst I – Reporting & Operations

Impact you will make

You’ll turn raw data into reliable, decision-ready insights. You’ll own standard dashboards and recurring reports, improve data quality at the source, and deliver clear recommendations that help leaders optimize performance, client outcomes, and growth.

What you will do

• Own daily/weekly/monthly reports for business and client KPIs with defined SLAs.
• Build, enhance, and automate Tableau dashboards and Excel trackers (KPIs, financials, aging, productivity).
• Reconcile data across systems; investigate root causes; drive fixes with data owners.
• Translate ad-hoc asks into well-scoped analyses with context and actionable takeaways.
• Partner with QA, Finance, Operations, and Client Services on validation, productivity analysis, and staffing forecasts.
• Maintain data integrity standards; document sources, definitions, and assumptions.
• Identify and prioritize process improvements to reduce manual work and improve timeliness.
• Contribute to and maintain reporting documentation and SOPs as needs evolve.

What you will bring

• Bachelor’s in Business, STEM, or related field (or equivalent experience).
• 1–3 years in data/analytics (internships/co-ops count; strong projects welcomed).
• Intermediate SQL (joins, CTEs, window functions; troubleshooting mismatches).
• Strong Excel (formulas, pivot tables, lookups; basic automation/macros a plus).
• Hands-on Tableau or Power BI experience building and refining dashboards.
• Ability to work with large datasets, translate questions into queries, and explain results to non-technical partners.
• Clear, concise communication; comfort managing multiple deadlines.

What we would like to see

• Experience in healthcare revenue cycle or operational analytics.
• Familiarity with hospital/billing systems (Epic, ARO, CM, etc.).
• Track record of improving a reporting process (e.g., automation, data quality fix).
• Strong organization and prioritization for recurring vs. urgent ad-hoc work.
• Collaborative mindset and ownership attitude.