Product Development
Overview We are seeking a highly skilled Data Analyst to design, develop, and deliver actionable analytics for a cloud-native US Healthcare Revenue Cycle Management (RCM) platform. This role focuses on data analysis, BI, dashboards, automation, and reporting across Claims, Prior Authorization, Scheduling, Coding, Collections, Payments, Denials, AR, and EDI. You will work closely with Product, Engineering, Data Engineering, DBA, AI/ML, RPA, DevOps, Compliance, and Operations teams to deliver real-time, secure, and compliance-ready analytics.
Job Roles & Responsibilities
Data Analysis & Reporting
- Analyze operational, financial, and clinical data across RCM workflows to provide actionable insights.
- Write advanced SQL queries and generate reports from SQL Server, Snowflake, and Redshift.
- Develop Power BI dashboards and reports for internal teams and external stakeholders.
- Leverage Excel, Power Query, pivot tables, and formulas for deep-dive analysis.
- Prepare stakeholder-ready PowerPoint presentations and Word documentation summarizing trends and insights.
AI/ML & Automation Enablement
- Collaborate with AI/ML, GenAI, Agentic AI, and RPA teams to provide curated datasets for model training and validation.
- Build dashboards tracking predictive insights, AI model outputs, and automation exceptions.
- Enable actionable insights to trigger operational workflows through Power Automate and enterprise automation.
RCM & EDI Analytics
- Work with Claims, Prior Authorization, Coding, Collections, Payments, Denials, AR, and EDI (837, 835, 270/271, 276/277, 278) data to deliver operational intelligence.
- Conduct root-cause analysis to identify revenue leakage, payer performance issues, and process inefficiencies.
Collaboration & Stakeholder Engagement
- Partner with Product Managers, Operations, Finance, and AI/ML teams to align analytics with business goals.
- Support self-service analytics adoption for operational and management teams.
- Communicate insights effectively using data storytelling, dashboards, and presentations.
Data Governance & Compliance
- Ensure analytics solutions comply with HIPAA, SOC 2, and internal security policies.
- Implement role-based access controls (RBAC), PHI masking, and audit-ready reporting.
- Document data sources, metrics definitions, and reporting logic to maintain traceability.
Experience
- Bachelor’s or Master’s degree in Data Analytics, Statistics, Computer Science, Information Systems, or related fields.
- 3-6+ years of experience in data analysis, BI, or analytics roles.
- Hands-on experience with Power BI, Tableau, SQL Server, Snowflake, Redshift.
- Strong proficiency in Excel, Power Query, pivot tables, formulas, and PowerPoint presentations.
- Exposure to AI/ML, GenAI, Agentic AI, or RPA-driven analytics is a plus.
- Experience in US Healthcare, RCM, or other regulated domains is preferred.
Technical Expertise
- Databases & Querying: SQL Server, Snowflake, Redshift, PostgreSQL, Advanced SQL
- BI & Visualization Tools: Power BI, Tableau, Looker, Power Automate
- RCM & EDI Analytics: 837, 835, 270/271, 276/277, 278
- AI/ML & Automation: Dashboarding for model outputs, predictive analytics, RPA workflow monitoring
- Cloud Awareness: AWS, Azure, GCP (analytics & security awareness)
- Data Governance & Security: HIPAA, SOC 2, RBAC, PHI masking, audit-ready reporting
- Office Productivity: Advanced Excel, PowerPoint, Word, including pivot tables, formulas, dashboards, and presentations
- Integration & Pipelines: Microservices, APIs, event-driven data pipelines
Skillset
- Strong data analysis, problem-solving, and visualization skills.
- Ability to translate complex RCM workflows, AI outputs, and analytics into actionable insights.
- Experience collaborating with cross-functional teams including AI, RPA, DevOps, and product.
- Excellent communication, presentation, and stakeholder engagement skills.
- Attention to detail, compliance awareness, and audit-ready reporting mindset.
Strategic Impact
- Deliver accurate and actionable analytics to improve operational efficiency, collections, and payer transparency.
- Support AI/ML adoption and automation workflows with curated data and performance dashboards.
- Enable real-time insights and data-driven decision-making across RCM modules.
- Improve operational KPIs, reduce revenue leakage, and strengthen compliance and audit readiness.