QC Specialist Data Analytics

Dublin
11 months ago
Applications closed

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Associate Data Scientist

QC Specialist Data Analytics

Team Horizon is seeking a QC Specialist Data Analytics for our client based in Dublin who will have a key role in Quality Transformation and the QC Optimization Initiative. The role will be responsible for applying advanced data analytics to extract actionable insights, optimize QC workflows, and drive digital transformation in quality operations.

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!

Why you should apply:

  • This is an excellent opportunity to join a world class manufacturing operation, with an outstanding track record of reliably delivering high-quality medicines to patients around the world suffering serious illnesses.

  • There is a strong culture of continuous improvement and innovation within the company to strive for solutions that improve health outcomes and dramatically improve people’s lives.

  • Our client is developing the capability to produce all its medicines in Dublin, helping to ensure continuity of supply of our medicines as they expand internationally.

    What you will be doing:

  • 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 dat management and accessibility.

  • Drive innovation in digital QC strategies, leveraging big data analytics for enhanced quality monitoring and predictive quality insights.

    What you need to apply:

  • 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 to have a 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

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