Quality Analytics Lead - Medical Devices

Abbott (abbottcareers2 board); United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Abbott is seeking a Quality Assurance Lead Specialist in Sylmar, CA for onsite work focusing on quality analytics and regulatory compliance. You will independently conduct advanced analytics, lead cross-functional data initiatives, and develop dashboards and reports to improve quality and reduce risk.

The role requires a strong background in statistics, data science, and quality systems, with experience in CAPA, complaints, and post-market surveillance.

Qualifications

• Bachelor’s degree in life sciences or engineering required.
• Regulated industry experience (medical devices/pharma) preferred.
• Strong programming and data analysis skills with Python/R/SQL/SAS.
• Experience with data governance and regulatory compliance highly valued.

Responsibilities

• Independently execute advanced quality data analytics with minimal supervision.
• Lead cross-functional data-driven initiatives for quality improvement.
• Analyze large datasets from CAPA, complaints, nonconformances, and more.
• Develop analytical solutions to address quality and operational challenges.
• Apply machine learning and predictive analytics to detect quality issues.
• Design dashboards and automate quality performance reports.
• Mentor analysts and collaborate with Quality, Operations, Engineering, Regulatory.
• Support regulatory inspections and quality system monitoring.

Skills

Python

R

SQL

SAS

Data analytics

Machine learning

Statistics

Data visualization

Power BI

Quality analytics

Education

Bachelor's degree in life sciences or engineering

Preferred degree in data science / statistics / CS

Tools

Infinity QS

Job description

Abbott is seeking a Quality Assurance Lead Specialist in Sylmar, CA for onsite work focusing on quality analytics and regulatory compliance. You will independently conduct advanced analytics, lead cross-functional data initiatives, and develop dashboards and reports to improve quality and reduce risk.

The role requires a strong background in statistics, data science, and quality systems, with experience in CAPA, complaints, and post-market surveillance.