The Principal Analyst, Quality & Compliance provides leadership for compliance and quality activities across Biometrics. He/She is responsible for addressing compliance requests and questions, for ensuring inspection readiness and for providing quality and compliance training to the Biometrics department. He/She plays a pivotal role supporting closure of the most complex and important regulatory agency commitments and CAPAs specific to Biometrics. He/She consults and provides guidance for other departments on Biometrics specific quality regulations, expectations, and best-practices.
1.Provide guidance and support to Biometrics staff in the area of regulatory compliance and best practices. Serve as a liaison between Biometrics and R&D Quality and Compliance. Assist with CAPAs, Memos to file, deviations and other compliance related items. Maintain expertise in regulations, guidance and best practices related to data integrity and all Biometrics activities.
2.Coordinate Biometrics-related internal and external audits and inspections. Provide leadership, training and support to inspection teams. Support closure of regulatory agency commitments and CAPAs specific to Biometrics.
3.Lead and/or contribute to Biometrics and cross-functional initiatives related to quality and compliance. Participate in the identification of gaps in process or documentation and leads teams to implement solutions.
4.Provides training on regulations, expectations, and best-practices.
10+ years relevant work experience in related position(s) with a focus on data management and/or data analysis
Expertise in global industry regulations and best practices (E.g. Data Integrity, GCP, 21 CFR Part 11)
Experience with regulatory inspections
Experience with Quality Management Systems
Deep understanding of drug development and biopharmaceutical industry
High attention to detail including proven ability to manage multiple, competing priorities, must have excellent negotiation and problem-solving skills
Bachelor's degree, preferably in a scientific discipline such as Statistics, Mathematics, Economics, Computer Science, IT, Biology, Social Science, etc.