Role Overview

RagaAI is looking for a detail-oriented and tech-savvy Data Operations Specialist to manage, label, and transform internal datasets with a strong focus on healthcare data. This role plays a critical part in maintaining data integrity across multiple systems—including back-end platforms, Electronic Health Records (EHRs), and large-scale spreadsheets.

A significant portion of this role involves data labeling and tagging, where you will identify patterns, correct inconsistencies, and prepare high-quality datasets for analytics and AI model training.

Key Responsibilities

• Multichannel Data Entry: Accurately enter and validate data across back-end applications, EHR systems, and cloud-based platforms.
• Data Labeling & Tagging: Review healthcare-related text and image datasets, apply accurate labels, identify anomalies, and flag inconsistencies.
• Spreadsheet Management: Create, maintain, and audit large datasets using Microsoft Excel and Google Sheets, leveraging advanced functions such as VLOOKUP, Pivot Tables, and conditional logic.
• Data Cleaning & Transformation: Clean raw datasets by removing duplicates, correcting formatting issues, and converting data into structured, analysis-ready formats.
• Quality Assurance: Conduct routine data audits to ensure accuracy, consistency, and compliance with healthcare and data governance standards.

Required Skills & Qualifications

• Experience: 2+ years of experience in data operations, data entry, or data annotation.
• Technical Skills: Advanced proficiency in Microsoft Excel and Google Sheets.
• Systems Exposure: Hands-on experience working with back-end systems and/or EHR platforms.
• Analytical Ability: Strong attention to detail with the ability to identify and resolve errors in large datasets efficiently.
• Healthcare Exposure (Preferred): Familiarity with medical terminology, HIPAA compliance, or clinical workflows is a plus.

Preferred Attributes

• Exceptional attention to detail—accuracy and precision are critical.
• Ability to work independently with minimal supervision.
• Strong organizational and time-management skills to handle multiple data streams effectively.