Work Schedule
7 1/2 hr shift
Environmental Conditions
Adherence to all Good Manufacturing Practices (GMP) Safety Standards, Office, Some degree of PPE (Personal Protective Equipment) required (safety glasses, gowning, gloves, lab coat, ear plugs etc.)
Job Description
Our Whitby Site specializes in commercial manufacturing for a full range of conventional dosage forms with specialized capabilities, and houses a fully integrated pharmaceutical development services (PDS) facility.
Discover Impactful Work:
The CPV & Data Sciences Leader exists to ensure manufacturing processes remain consistently controlled, compliant, and continuously improving by leveraging data science and digital tools. The role drives the design and
execution of Continued Process Verification (CPV) programs while translating complex process data into actionable insights that improve product quality and performance. It also enables the adoption of advanced
analytics, dashboards, and AI-driven monitoring to proactively detect risks and optimize operations. Ultimately, the position bridges manufacturing, quality, and digital teams to deliver scalable, data-driven decision-making across
the process lifecycle.
Day in the Life:
• 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
across the organization.
• Ensure all activities comply with Good Manufacturing Practices (GMP), data integrity principles, and internal quality systems.
Key to Success:
Education:
• 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.,
ALCOA+)
Experience:
• Minimum of 3 years of experience in pharmaceutical manufacturing, Manufacturing Science and Technology
(MSAT), process validation, or data analytics within a Good Manufacturing Practices (GMP) environment
• 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
Equivalency:
• Equivalent combinations of education, training, and relevant work experience may be considered
Knowledge, Skills, and Abilities:
• 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
Physical Requirements:
Position requires ordinary ambulatory skills and physical coordination sufficient to move about lab/lab office
locations; ability to stand, walk, stoop, kneel, crouch periodically for prolonged periods of time; manipulation (lift,
carry, move) of light to medium weights of 10-35 pounds; arm, hand and finger dexterity, including ability to grasp and type for prolonged periods of time; visual acuity to use a keyboard, computer monitor, operate equipment, and
read materials for prolonged periods of time; ability to sit, reach with hands and arms, talk, and hear for prolonged
periods of time. Use of Personal Protective equipment may be required and may include any of the following:
Safety glasses, safety shoes, lab coat, latex or similar gloves, safety apron, organic respirator occasionally.
Excellent Benefits
OTHER
- 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
Compensation
The salary range estimated for this position based in Ontario is $69,400.00–$104,050.00.