Senior Analytics & Insights Associate

Vizient•Chicago, IL

1d•$88,900 - $155,500

About The Position

In this role, you will lead the execution of complex healthcare analytics projects that translate client needs into well-defined analytic methodologies, data requirements, and actionable insights. You will navigate complex analytical and data challenges while collaborating with the Life Sciences & Industry Solutions (LSI) and Research Analytics and Insights (RAIN) teams, business consultants, statisticians, and other subject matter experts to deliver high-quality analyses that support strategic decision-making, clinical quality improvement, and real-world evidence generation.

Requirements

5 or more years of relevant experience required.
Experience working with healthcare clinical, administrative, claims, or similar datasets required.
Advanced SQL and relational database skills highly preferred.
Strong knowledge of the healthcare provider and/or payer environment preferred.
Experience with Databricks preferred.

Nice To Haves

Relevant degree preferred. Advanced degree in Healthcare Administration, Health Informatics, Data Analytics, or related field preferred.
Experience with Vizient Clinical Database, Operational Database, Procedural Analytics, or other Vizient data products highly preferred.

Responsibilities

Lead the execution of complex analyses using large healthcare clinical, administrative, claims, and other relevant datasets.
Develop and document advanced analytic methodologies, including patient and provider cohorts, custom outcome definitions, segmentation approaches, and project-specific analytical logic.
Develop, troubleshoot, and optimize advanced SQL queries across relational databases, data products, and platforms.
Investigate complex data anomalies, unexpected results, and edge cases; evaluate potential solutions and recommend appropriate approaches.
Translate complex client needs and business questions into clear analytic requirements, methodologies, and deliverables.
Collaborate with business consultants, statisticians, and other subject matter experts to align analytic methodologies and data definitions with project objectives.
Identify project risks, data limitations, methodology questions, and potential timeline impacts and recommend solutions proactively.
Apply rigorous data-quality and quality-assurance practices to validate analytic outputs and ensure accurate, reliable deliverables.
Provide analytic guidance and share best practices to support consistent, high-quality execution across projects.
Use approved generative AI tools, including Databricks Genie, to improve efficiency and quality across SQL development, documentation, research, methodology development, and quality assurance.