Analyze 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, predictive quality insights and emerging Gen AI capabilities.
Qualifications:
Bachelor's or Master's degree in a relevant field such as Computer Science, Data Analytics Chemistry, Biochemistry, Pharmaceutical Sciences, Engineering, or a related discipline.
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.
