CPV & Data Sciences Specialist

• Lead the design, implementation, and lifecycle management of Continued Process Verification (CPV) programs across manufacturing processes.

• Define and monitor Critical Quality Attributes (CQAs) and Critical Process Parameters (CPPs) using statistical and risk-based methodologies.

• Analyze manufacturing and quality data using statistical tools to identify trends, variability, and potential risks impacting process performance.

• Develop and maintain dashboards and reports using digital tools (e.g., Discoverant and Power BI) to enable real-time process monitoring and decision-making.

• Oversee data collection, integration, and trending from manufacturing systems such as Manufacturing Execution Systems (MES), Laboratory Information Management Systems (LIMS), and data historians.

• Support investigations related to deviations, Out-of-Specification (OOS) results, and process trends by performing root cause analysis and providing data-driven insights.

• Collaborate with Manufacturing Science and Technology (MSAT), Quality, Engineering, Automation, and Information Technology (IT) teams to align CPV strategies with site and global objectives.

• Act as the site Subject Matter Expert (SME) for Discoverant, including system configuration, user support, troubleshooting, and continuous improvement.

• Implement and support advanced analytics, including artificial intelligence (AI) and machine learning (ML) models, to enhance process monitoring and predictive capabilities.

• Translate complex datasets into clear, actionable insights and documentation to support regulatory submissions, audits, and inspections.

• Define and track key performance indicators (KPIs) to ensure ongoing process control, compliance, and continuous improvement.

• Mentor and provide technical guidance to team members in CPV, data analytics, and digital tools.

• Drive adoption of digital manufacturing solutions and promote a culture of data-driven decision-making

• Ensure all activities comply with Good Manufacturing Practices (GMP), data integrity principles, and internal quality systems.

• Minimum Bachelor’s degree in engineering, Data Science, Statistics, Pharmaceutical Sciences, or a related field

• Training or certification in data analytics, statistical analysis, or data science tools (e.g., Python, Minitab, Discoverant, JMP, PowerBI, or SAS)

• Knowledge of regulatory guidelines and frameworks (e.g., Food and Drug Administration (FDA), European Medicines Agency (EMA), and International Council for Harmonisation (ICH))

• Familiarity or certification in Good Manufacturing Practices (GMP) and data integrity principles (e.g.,

• Minimum of 3 years of experience in pharmaceutical manufacturing, Manufacturing Science and Technology

• Experience applying Continued Process Verification (CPV) principles in support of process monitoring and lifecycle validation

• Experience performing statistical analysis and using data science tools (e.g., Python, R, JMP, or SAS) in manufacturing or quality settings

• Experience working with manufacturing data systems such as Manufacturing Execution Systems (MES), Laboratory Information Management Systems (LIMS), or data historians

• Experience supporting investigations (e.g., deviations or Out-of-Specification (OOS) results) using datadriven approaches, including internships or co-op placements in relevant industries

• Equivalent combinations of education, training, and relevant work experience may be considered

• Strong knowledge of Continued Process Verification (CPV), process validation lifecycle, and regulatory expectations (e.g., Food and Drug Administration (FDA), European Medicines Agency (EMA), and International Council for Harmonisation (ICH))

• Expertise in statistical analysis, data science methodologies, and multivariate analysis techniques

• Proficiency with data analytics and visualization tools (e.g., Python, R, JMP, SAS, Discoverant, and Power BI)

• Understanding of manufacturing data systems, including Manufacturing Execution Systems (MES) and Laboratory Information Management Systems (LIMS)

• Knowledge of data integration and data modeling

• Strong analytical and problem-solving skills with the ability to interpret complex datasets and identify root causes

• Ability to translate technical data into clear, actionable insights for cross-functional stakeholders

• Strong leadership, collaboration, and influencing skills in a cross-functional environment

• Ability to manage multiple priorities and drive projects in a fast-paced, regulated environment

• Commitment to Good Manufacturing Practices (GMP) and data integrity principles (e.g., ALCOA+)

• Ability to support continuous improvement initiatives and drive digital transformation and innovation

• Detail oriented and organized, with a high degree of accuracy and thoroughness.

• Good/Excellent organizational skills and ability to prioritize in a face-pace environment.

• Demonstrated computer proficiency with Microsoft Office programs.

• Proficiency with the English Language

• Medical, Dental, & Vision benefits-effective Day 1
• Paid Time Off & Designated Paid Holidays
• Retirement Savings Plan
• Tuition Reimbursement

• Relocation assistance is NOT provided
• Must be legally authorized to work in Canada now or in the future, without sponsorship
• Must be able to pass a comprehensive background check

Thermo Fisher Scientific