Director, Quality Analytics

Director, Quality Analytics

Responsibilities
- Partner with Quality and business leadership to implement integrated analytics and governance for GxP compliance, process performance, risk signals, and resource utilization.
- Establish and maintain a scalable Quality metrics framework (KPI library/definitions, calculation logic, refresh cadence, ownership, reporting standards).
- Lead analytics prioritization and demand management (intake, triage, roadmap, delivery, sustainment), balancing strategic and operational needs.
- Develop governed dashboards, scorecards, and semantic models for controlled self-service insights.
- Integrate multi-source datasets and automate recurring reporting to reduce manual effort and improve speed-to-insight.
- Apply data science methods (statistical modeling, forecasting, anomaly/trend detection, process capability, risk scoring) to identify issues and opportunities.
- Operationalize analytics products (model + pipeline + monitoring) and measure sustained impact.
- Establish and scale NLP to extract structured insights from unstructured Quality content for trending, classification, summarization, and knowledge discovery.
- Identify and deliver prioritized LLM-enabled Quality use cases using approved enterprise platforms.
- Enable governed datasets and pipelines in platforms such as Snowflake/enterprise data environments with secure access and governance.
- Promote “right-first-time” data practices by improving data standards, completeness, and consistency with process/system owners.
- Develop team capability across BI/analytics engineering, data science, NLP, and GenAI/agentic AI, including training and skill progression.
- Build, lead, and develop a high-performing team with clear goals, priorities, and expectations.
- Drive analytics adoption through structured change management.

Qualifications (Education & Experience)
- PhD or Master’s in a data-related field with substantial engineering, business, and statistical component.
- 10+ years’ experience in pharmaceutical/biotechnology/healthcare/health IT; 3+ delivering end-to-end data analysis projects (or equivalent).
- Demonstrable experience in pharma/biotech/device solving business and/or compliance challenges via analytic approaches (strongly preferred).
- Experience with Veeva QMS and other eQMS systems (preferred).

Knowledge & Skills (Required/Preferred)
- Turn data into decision-grade information.
- Data modeling; advanced analytics tools (Python, R, SAS, SQL, Alteryx).
- Data visualization (Spotfire, Power BI, and/or Tableau).
- NLP on unstructured text (classification, extraction, summarization, search).
- Data platforms such as Snowflake/enterprise ecosystems; partner with data engineering.
- Data governance and data quality (definitions/standards, lineage, monitoring, stewardship collaboration).
- Experience designing/deploying LLM-enabled solutions on enterprise platforms.
- Scripting languages to leverage APIs (e.g., REST APIs).
- Strong communication (oral, written, presentation).
- Understanding of Quality Management System requirements and regulated-environment best practices.
- Leadership with change management; adaptability/resourcefulness.
- Strong problem solving, critical thinking, and analytical/data analysis skills.
- Experience executing adoption plans with communications, stakeholder engagement, and readiness activities.