Business Quality Analyst - Clinical & R&D

Job Summary:

We are seeking an experienced Business Quality Analyst with a strong background in Clinical R&D. The ideal candidate will have deep domain expertise in end-to-end R&D and clinical workflows, ensuring that business requirements align with industry standards and regulatory compliance. In this role, you will work closely with stakeholders across clinical operations, regulatory, and quality teams to identify, analyze, and optimize processes, enhancing data quality and ensuring seamless workflow integration.

Key Responsibilities:

- Analyze, document, and optimize clinical and R&D workflows to align with business and regulatory requirements.

- Collaborate with cross-functional teams (clinical, regulatory, IT, and business) to gather, interpret, and document business requirements, ensuring alignment with industry standards.

- Conduct end-to-end quality assessments across clinical and R&D processes, identifying areas for improvement and recommending solutions to enhance quality and compliance.

- Develop and execute test plans to validate data integrity and workflow accuracy.

- Serve as a liaison between technical teams and business stakeholders to ensure seamless integration of R&D and clinical systems and tools.

- Provide ongoing analysis of data quality and regulatory compliance throughout the project lifecycle.

Requirements:

- Bachelor's degree in Life Sciences, Biotechnology, Computer Science, or related field; advanced degree preferred.

- 12+ years of experience as a Business Quality Analyst, ideally within Clinical or R&D domains.

- Strong understanding of end-to-end clinical R&D workflows and regulatory requirements in life sciences.

- Proven expertise in quality assurance, data integrity, and compliance within clinical and R&D environments.

- Excellent analytical, communication, and stakeholder management skills.

- Proficiency with workflow management and data analysis tools (e.g., SQL, JIRA, MS Project).

Preferred Qualifications:

Knowledge of Agile methodology and experience in project management. Familiarity with AI and machine learning applications within clinical R&D.