Lab Process & Innovation Specialist

The Lab Transformation Specialist drives lab transformation projects across both CPSNA sites, leveraging new technology, artificial intelligence, and continuous improvement methodology to modernize how the lab operates without compromising quality or compliance. This role leads the lab's end-to-end transformation — equipment, workflow, data, and the way work gets done — while safeguarding the integrity of the quality systems that govern it. It leads Lean/Six Sigma process improvement initiatives, evaluates and validates new laboratory equipment and technology through formal IQ/OQ/PQ qualification. The role also owns lab data analytics, ensuring lab data is captured, traceable, and available in real time in accordance with data integrity (ALCOA+) principles, to support faster, risk-based decision-making across both sites. The Lab Transformation Specialist supports compliance with GLP, ISO 17025, and other applicable standards, drives standardization across both sites, and serves as the primary point of contact for lab transformation, technology, and data initiatives across CPSNA.

Key duties/responsibilities:

Process Improvement

• Lead lab transformation projects across both sites, applying Lean/Six Sigma and continuous improvement methodology to laboratory workflows without compromising GLP compliance, data integrity, or quality standards.

• Facilitate kaizen events, value stream mapping, and workflow redesign to reduce sample turnaround time and non-value-added steps in testing and disposition workflows.

• Support broader lab process improvements identified by site teams, department leads, and analysts across both sites, ensuring changes are documented and validated in line with quality system requirements.

• Build and maintain a continuous improvement pipeline with measurable targets for testing throughput, right-first-time quality, and turnaround time.

Equipment & Technology Validation

• Evaluate, pilot, and help select new laboratory equipment and analytical technology.

• Lead capital equipment projects from business case through installation, formal IQ/OQ/PQ qualification, and handoff to lab operations, ensuring instruments are audit-ready before release for use.

• Implement new lab equipment and technology and directly support analysts through the validation process, ensuring qualification protocols, calibration records, and supporting documentation meet GLP and QMS standards.

• Maintain a technology roadmap for both sites, identifying automation, AI, and modernization opportunities that improve testing capability without introducing compliance risk.

• Lead the introduction and expansion of inline testing equipment across lab and manufacturing operations, reducing reliance on manual and off-line testing.

AI, Data Analytics & Predictive Modeling

• Own lab data analytics across both sites, ensuring lab data is captured, integrated, and available in real time — with full traceability and adherence to data integrity (ALCOA+) principles — to support faster, risk-based decision-making.

• Develop trending, dashboards, and data-driven insights from lab systems (LIMS/SAP) to surface out-of-trend and quality signals proactively, supporting risk-based testing strategies rather than reactive investigation.

• Identify and pilot AI, predictive modeling and automation opportunities that reduce manual testing and improve turnaround time, in partnership with site lab and quality leadership, while maintaining method validity and regulatory defensibility.

Cross-Site Standardization

• Standardize testing procedures, workflows, technology, and data practices across Atlanta and Puerto Rico, ensuring consistent quality outcomes regardless of site.

• Ensure new equipment, technology, and data initiatives are implemented consistently, validated, and integrate cleanly with existing quality systems across both sites.

Change Management

• Lead stakeholder communication and training plans for new equipment, technology, and process rollouts.

• Track adoption and sustainment of process and technology changes post-implementation, adjusting approach based on results.

Global & Cross-Functional Engagement

• Support and lead global lab transformation projects, representing CPSNA (both sites) within the broader CPS Global Laboratory network.

• Implement global transformation initiatives at each site, adapting global standards and technology to local site conditions while maintaining alignment with the enterprise roadmap.

• Collaborate with and influence global and local stakeholders to ensure CPSNA transformation work reflects and contributes to CPS Global Laboratory priorities.

Job Requirements/Qualifications

Number of years of previous work experience required:

• Minimum 5+ years of experience in a laboratory, quality, or manufacturing environment, with a focus on process improvement, Lean/Six Sigma, or lab technology.

• Experience leading capital equipment or technology projects, including IQ/OQ/PQ qualification protocols in a GLP or regulated laboratory environment, strongly preferred.

• Experience with lab data analytics, AI/predictive modeling, or laboratory informatics strongly preferred.

Education

• Bachelor's degree in a scientific discipline (Chemistry, Biology, Food Science, or related), engineering, or data/information systems, or equivalent experience.

• Preferred Master’s Degree in Project Management or similar field, and/or PMP certification.

Technical skills

• Lean or Six Sigma certification (Green Belt or higher) strongly preferred.

• Experience evaluating, piloting, implementing, and qualifying new laboratory equipment and analytical technology, including IQ/OQ/PQ protocols, in a GLP-compliant environment.

• Working knowledge of ISO 17025 laboratory accreditation requirements and quality management systems.

• Working knowledge of GLP (Good Laboratory Practices) and GDocP within a regulated manufacturing environment.

• Data analytics skills, including building dashboards, trending, and real-time data reporting from lab systems (LIMS/SAP or equivalent), with an understanding of data integrity (ALCOA+) principles.

• Familiarity with AI and predictive modeling concepts as applied to inline testing and release decision support.

• Ability to build and maintain a technology roadmap and continuous improvement pipeline with measurable quality and efficiency targets.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class.