Full Description

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Summary

• In this role, you will specialize in analytics and have a critical role in ensuring the accuracy, integrity, and reliability of Vizient’s data-driven products and insights. You will apply Agile and Software Development Lifecycle (SDLC) QA (Quality Assurance) methodologies to validate functional software components and the analytical outputs they generate. You will ensure that business intelligence dashboards, predictive models, and data pipelines meet quality standards and deliver trustworthy insights that support decision-making across the healthcare ecosystem.

Responsibilities

• Analyze requirements, data flows, and design specifications to create comprehensive test strategies that emphasize analytical accuracy and data validation.
• Design, execute, and maintain test plans that cover data quality, transformation logic, aggregation rules, and business logic validation in addition to functional and regression testing.
• Develop and maintain automated test scripts for data validation and analytical pipelines using tools such as Selenium, or Python-based frameworks.
• Validate Extract, Transform, Load (ETL) processes, reporting layers, and dashboards; ensuring consistency of Key Performance Indicators (KPIs), metrics, and visualizations with underlying data sources.
• Write complex SQL/PL-SQL queries to validate data integrity, and ensure analytical outputs are aligned with business requirements.
• Partner with data engineers and business intelligence developers to verify model accuracy, statistical outputs, and integration of analytical components.
• Support validation of AI/ML models by testing input/output integrity and ensuring model-driven insights are aligned with business logic.
• Identify data anomalies, conduct root cause analysis, and recommend improvements in data collection, transformation, and presentation.
• Track, manage, and prioritize defects related to data accuracy and analytics, collaborating with technical and business teams for resolution.
• Provide recommendations to enhance data governance, reporting consistency, and analytical system scalability through QA best practices.
• Contribute to the creation of regression suites for recurring analytics validation, ensuring accuracy across multiple releases

​Qualifications