Data Analyst

Company Description

Today, an Indian hospital revenue is largely dominated by Insurance payers - Govt + Private. With 200+ payers in the mix, the overall revenue cycle management (RCM) in India is broken, opaque, and complex filled with unexpected shortfalls and delayed realizations.

At Care.fi, we are building India’s first AI-led RCM platform for hospitals which will enable them to solve these pitfalls and thereby improving margins. Backed by marquee investors such as Peak XV (erstwhile Sequoia India) we are already a trusted partner for top Indian brands including Apollo, Fortis, Narayana Health, and Aster Group.

About the Role

Data Analyst

Key Responsibilities

• Data Extraction & Analysis:

  Write complex SQL queries to extract, manipulate and analyze large datasets from multiple sources.

• Business Insights:

  Develop dashboards, reports and visualizations to provide actionable insights to business teams.

• Data Validation & Quality:

  Ensure data integrity, accuracy, and consistency across all reporting platforms.

• Performance Tracking:

  Monitor key business metrics, identify trends, and recommend data-driven solutions.

• Process Optimization:

  Automate data workflows and reporting processes for improved efficiency.

• Collaboration:

  Work closely with business, product, and engineering teams to understand data requirements and drive business impact.
• Take ownership of end-to-end data projects and deliver them with accuracy and speed.

Required Skills and Qualifications

• Experience:

  Minimum 5 years of experience as a Data Analyst
• SQL (Mandatory) – Strong expertise in writing optimized queries for large datasets
• Experience with data visualization tools such as Power BI, Tableau or Looker is a plus
• Proficiency in Excel for data analysis and reporting

• Analytical Skills:

  Strong problem-solving abilities and experience in deriving business insights from data

• Communication Skills:

  Ability to present findings and insights in a clear and actionable manner

• Attention to Detail:

  Strong focus on data accuracy, validation, and process optimization