Quality Analyst II

Quality Analyst II

An employer is seeking a Quality Analyst II for a remote long term opportunity with a leader in the medical device industry. This quality analyst will support the Post Market Surveillance (PMS) organization through advanced statistical analysis, software validation, data visualization, and process optimization efforts. This individual will analyze post-market product data, develop and maintain analytical tools, create regulatory and management reporting, and support ongoing quality and compliance initiatives across Medical device business units. The ideal candidate combines strong technical expertise in R programming, data analytics, software validation, and database querying with a background in quality systems and medical device or regulated environments.

Key responsibilities will include: review and analyze post-market surveillance data across multiple product lines to identify trends, quality signals, and emerging risks. Develop, maintain, and enhance statistical models, computational scripts, and analytical tools using R and the Tidyverse ecosystem. Design and build interactive dashboards and reporting solutions using R Shiny and advanced data visualization techniques. Generate monthly complaint trending reports and other post-market surveillance deliverables for leadership review. Support signal detection activities through statistical analysis and presentation of findings to stakeholders. Execute ad hoc statistical analyses and reporting requests to support quality, regulatory, and business needs. Participate in software validation activities, including protocol development, testing, documentation, and compliance support. Create and maintain SQL queries to extract, transform, and validate data from enterprise systems. Utilize advanced Excel functionality for data analysis, validation, reporting, and process improvement initiatives. Manage project activities and documentation within Jira, ensuring deliverables and timelines are met. Collaborate with Quality, Regulatory Affairs, Data Science, and business stakeholders to improve surveillance processes and reporting capabilities. Support continuous improvement initiatives by identifying opportunities for automation, standardization, and enhanced data-driven decision making.