We are seeking an experienced automation QA professional to develop test automation frameworks and ensure the quality of AIR’s scientific and financial analytics software. You will collaborate with cross-functional teams, improve testing practices, and mentor junior team members.

Responsibilities
• Design, develop, and maintain object-oriented test automation frameworks and scripts.
• Define test plans and milestones, and participate in requirements and technical reviews.
• Validate product functionality, data accuracy, and scientific or financial calculations.
• Develop SQL scripts for database validation and test data preparation.
• Extend automation coverage throughout the software development lifecycle.
• Investigate complex issues and collaborate with teams to resolve defects.
• Mentor junior team members and promote automation best practices.

Qualifications
• 5+ years of QA experience in scientific or financial analytics software.
• 5+ years of programming experience in test automation, with proficiency in C#/.NET, Java, or PowerShell.




• Strong object-oriented programming and automation framework design skills.
• Hands-on experience with Selenium or comparable automation tools, BDD/Gherkin, and frameworks such as MSTest or VSTest.
• Robust SQL skills and knowledge of relational databases.
• Experience with Azure DevOps or AWS.
• Strong analytical, communication, and collaboration skills.

Our People, Our Culture

For more than 50 years, Verisk has helped property and casualty insurers make smarter decisions about risk through AI-powered risk modeling, advanced analytics, and technology solutions spanning the entire policy lifecycle. We are a leading strategic data, analytics, and technology partner to the global insurance industry, guided by core values of learning, caring, and results while maintaining the highest ethical standards as stewards of the industry's most comprehensive datasets. Learn more about Verisk and what we are doing within the insurance i

📌 Sr SDET II (Hyderabad)
🏢 Verisk
📍 Hyderabad