Lead Specialist Quality Assurance

Main Purpose of This Role

We are seeking a highly qualified Quality Assurance Lead Specialist in Sylmar, CA to conduct quality-related activities to deliver consistent, high quality documents, services, products and processes. Ensure compliance with world wide regulatory expectations/requirements. This is an ONSITE role.

What You'll Do

• Responsible for independently executing advanced quality data analytics and investigation activities with minimal management oversight.
• Lead cross-functional data-driven initiatives focused on quality improvement, risk reduction, process optimization, and regulatory compliance.
• Analyze large and complex datasets from CAPA, Complaints, Nonconformances, Supplier Quality, Manufacturing, and Post-Market Surveillance systems to identify trends, signals, and root causes.
• Develop innovative, practical, and compliant analytical solutions to address complex quality and operational challenges.
• Apply statistical methods, machine learning models, and predictive analytics to proactively detect emerging quality issues and support decision-making.
• Design, develop, and maintain dashboards, automated reports, and quality performance metrics to provide actionable insights across the organization.
• Demonstrate expertise in data science, statistical analysis, and quality systems while continuously expanding technical and leadership competencies.
• Identify opportunities for continuous improvement through data-driven analysis and recommend sustainable solutions.
• May provide technical guidance and mentorship to analysts, quality professionals, data scientists, and contractors.
• Maintain specialized expertise in Quality Analytics while leveraging knowledge of manufacturing, regulatory, engineering, and business processes.
• Collaborate closely with Quality, Operations, Engineering, Regulatory Affairs, Clinical, and Supply Chain teams to solve complex business problems.
• Represent the Data Science and Quality Analytics function on cross-functional projects and strategic initiatives.
• Implement tactical and strategic analytics activities to support quality objectives and business priorities.
• Contribute advanced statistical and data science expertise broadly across business functions.
• Directly influence project direction, investigation strategies, analytical methodologies, and quality risk management decisions through evidence-based insights.
• Support regulatory inspections, management reviews, CAPA effectiveness assessments, and quality system monitoring through robust data analysis and visualization.
• Ensure data integrity, governance, and compliance with applicable requirements including FDA 21 CFR Part 820, ISO 13485, and internal quality management system standards.

Qualifications

Education: Bachelors Degree (± 16 years) in life sciences or engineering or an equivalent combination of education and work experience. Preferred degree in Data Science, Statistics, Biostatistics, Computer Science, Engineering, Mathematics, Quality Engineering, or a related quantitative field.

Experience/Background: Minimum 4 years of experience applying data analytics, statistical modeling, and data science techniques in a regulated industry such as Medical Devices, Pharmaceuticals, Biotechnology, or Healthcare. Strong proficiency in Python, R, SQL, SAS, or similar analytical programming languages. Experience with machine learning, predictive analytics, anomaly detection, and pattern recognition methodologies. Advanced knowledge of statistical analysis techniques including hypothesis testing, regression analysis, multivariate analysis, survival analysis, DOE (Design of Experiments), SPC (Statistical Process Control), and time-series analysis. Experience working with large and complex datasets from Manufacturing, Quality Systems, Complaints, CAPA, Nonconformance, Supplier Quality, and Post-Market Surveillance systems. Proficiency with data visualization and business intelligence tools such as Power BI, Infinity QS. Experience developing interactive dashboards, automated reporting solutions, and executive-level data presentations. Strong understanding of data governance, data integrity, and validation principles in regulated environments. Demonstrated capability to translate complex analytical findings into actionable business recommendations.