QC Specialist Data Analytics

Overview

In this role, the candidate will join the Global Quality Control network and have a key role in E2E Quality Transformation and the QC Optimization Initiative.

We are seeking a highly skilled Quality Control (QC) Specialist with Data Scientist expertise to join our QC Network Team as a key contributor to the QC Digital Optimization Team. This role is critical to transforming the way QC laboratories and operations leverage data to enhance quality, efficiency, and compliance.

If you are passionate about Quality Control, laboratory analytics, and data science, and want to drive the next evolution of QC digital optimization, we encourage you to apply!

• Analyse and interpret complex QC data from laboratory instruments, manufacturing processes, and digital QC systems to improve decision-making and process efficiency.
• Collaborate with QC analysts to design and implement data-driven solutions for quality improvement and regulatory compliance.
• Assist in developing business cases and strategic recommendations for digital solution developments.
• Support the definition and advancement of a self-service reporting model. Automate QC reporting and visualization using tools such as Spotfire, Power BI, Tableau to provide real-time insights.
• Ensure data integrity and traceability by working with structured and unstructured QC datasets from multiple laboratory sources, including LIMS, LMES, and real-time monitoring systems.
• Optimize laboratory workflows by integrating digital tools, AI-driven analytics, and automation to enhance data collection and reporting efficiency.
• Partner with business stakeholders to share data best practices, identify and drive business process data standardization initiatives.
• Provide support in developing executive communications and present analysis and insights to senior leadership.
• Support analytical reports maintenance and validation.
• Work closely with IT, data engineering, and digital transformation teams to enhance QC data management and accessibility.
• Drive innovation in digital QC strategies, leveraging big data analytics for enhanced quality monitoring and predictive quality insights.

Basic Qualifications:

• Doctorate degree and 2 years of Project Management, Quality and/or Operations experience OR
• Master's degree and 6 years of Project Management, Quality and/or Operations experience OR
• Bachelor's degree and 8 years of Project Management, Quality and/or Operations experience.

Preferred Qualifications:

• Bachelor's or Master's degree in a relevant field such as Data Science, Chemistry, Biochemistry, Pharmaceutical Sciences, Engineering, or a related discipline.
• 5+ years of experience in Quality Control (QC) or Manufacturing setting, with a strong focus on QC data analysis and digital optimization.
• Deep knowledge of laboratory operations, analytical testing, quality control workflows, and regulatory requirements (e.g., GMP, GLP, FDA, ISO standards).
• Proficiency in programming languages with emphasis on SQL, Python and R.
• Experience with data visualization tools or packages, such as Spotfire, Power BI or Tableau.
• Experience with LIMS, MES, ELN, and other digital QC systems to extract, analyze, and interpret complex datasets
• Strong background in statistical data analysis, process monitoring, and root cause investigations in QC environments.
• Experience with advanced statistical/analytical techniques and machine learning algorithms (structured and unstructured data)
• Experience with Databricks platform for data analytics and MLOps
• Experience working with big data platforms, cloud-based analytics (AWS, Azure, GCP), and automation tools for QC data integration.
• Ability to translate complex QC datasets into actionable insights to enhance laboratory efficiency, compliance, and decision-making.
• Experience in pharmaceutical, biotech, medical device, or highly regulated industries where QC compliance is critical.
• Expertise in data governance, audit trail management, and data security best practices in a QC setting.
• Expertise in QC technology and digital transformation.
• Excellent Organisational, Communication Skills and Time Management.
• Ability to work under minimal supervision, identify and manage competing priorities.