Sr Data Analyst - Quality & Compliance

Role Overview

Sr Data Analyst – Quality & Compliance (Remote) You will be the sole data & analytics practitioner for the Animal Welfare and Integrity function, designing and operationalizing an enterprise-grade data and reporting framework that supports Quality Management Systems (QMS) and regulatory compliance.

What You’ll Do

Centralized quality data ecosystem

• Connect siloed QMS and compliance systems into a centralized, defensible data layer
• Enable risk-based decision-making using integrated quality and compliance data
• Build audit-ready workflows to support Quality, Compliance, Animal Welfare, Biosecurity, and Genetic Integrity programs

Data architecture & integration

• Integrate quality data sources including:
  • QMS, CAPA/RCCA, and non-conformance systems
  • Clinical, genetic, environmental, and biosecurity monitoring data
• Design validated data schemas and controls for auditability and regulatory defensibility
• Create lightweight ETL/ELT pipelines across databases, spreadsheets, and document-based systems

Risk and performance analytics

• Develop dashboards for leading and lagging quality risk indicators, including:
  • Deviation trends, recurrence, and velocity
  • Change control backlog, aging, approval cycle times
  • Training compliance drift
  • Repeat CAPAs and systemic failure patterns
• Build weighted risk indices to support risk-based prioritization and RCCA escalation
• Deliver executive-ready dashboards for Performance Integrity Review Boards and compliance leadership

Self-service reporting & conversational querying

• Provide self-service reporting and guardrails so teams can answer questions without ad-hoc data requests (e.g., deviations by quarter; USDA renewal status)
• Support dashboards and conversational AI interfaces for plain-language data questions

Workflow automation for compliance

• Automate regulatory protocol and documentation approvals/submissions, change control, and CAPA workflows:
  • Template generation and data auto-population
  • Approval routing and status tracking
  • Traceability across related quality and regulatory events
• Integrate automation into existing QMS platforms (not replacing them)
• Reduce manual effort, errors, and cycle time

Requirements

• Not explicitly stated in the provided text.

Nice-to-Haves

• Not explicitly stated in the provided text.