Cpl in partnership with our client Pfizer are seeking a Data Scientist: Process Modelling and Advanced AI (LLMs & Agentic Systems) to join the Join the team for a 12 month fixed term contract at their state of the art Dublin, Grange Castle site. This role carries a hybrid working model.
Data Scientist: Process Modeling and Advanced AI (LLMs & Agentic Systems)
The Manufacturing Intelligence (MI) team within Pfizer’s Global Technology & Engineering (GT&E) is responsible for driving the development and implementation of advanced analytics including AI/ML, soft sensors, advanced process control, and process condition monitoring solutions in support of manufacturing and future capabilities in Pfizer Global Supply (PGS).
As a member of MI, this role will have the opportunity to develop and implement cutting-edge AI technologies—including Large Language Models (LLMs), agent-based systems, real-time soft sensors, and advanced process control solutions—in manufacturing settings to identify actionable insights and continuous improvement in pharmaceutical manufacturing.
Responsibilities
• Technical contribution to high-impact projects that require data analytics, advanced modeling, and optimization expertise.
• Identify high-value opportunities for applying Advanced Analytics, Advanced Process Control (APC), Artificial Intelligence (AI), Machine Learning (ML), LLMs, Agentic AI, and the Industrial Internet of Things (IIoT), and develop and deploy innovative, fit-for-purpose solutions in the manufacturing environment.
• Drive development of mathematical models, machine learning systems, and LLM-based agentic workflows and support GMP implementation of these AI/ML solutions.
• Apply engineering principles, modeling tools, and experimental skills using data-rich lab/pilot/manufacturing equipment to improve process understanding and facilitate real-time process monitoring and control.
• Collaborate with cross-functional teams and key stakeholders, effectively communicate progress to management, and drive project advancement in a timely manner.
•Containerizing and Deploying models to production
Basic Qualifications
• An MSc or PhD degree in a relevant engineering major, mathematics, or computer science.
• Expert-level knowledge in Python is a must. Additional experience in any of the following languages is a plus: R, Matlab.
• Ability to perform data engineering on real-world big data, including structured time-series datasets with thousands of features.
• Demonstrated experience applying AI methodologies, including LLMs and agent-based architectures, to real-world data to generate insight and support decision making.
• Proven ability to build autonomous agents or AI copilots tailored to manufacturing or scientific workflows.
• Strong collaborator in diverse cross-functional teams, with a passion for innovation and continuous learning.
• Knowledge of Pharmaceutical (API) or Biopharmaceutical Manufacturing.
• Excellent oral and written communication skills, including the ability to translate technical concepts into actionable insight for both technical and non-technical audiences.
Preferred Qualifications
• Expertise in first-principles modeling (thermodynamics, reaction modeling, heat/mass transfer), hybrid modeling approaches, and the development of practical process models for real-time applications.
• Experience in cloud-based development environments such as AWS SageMaker.
• Familiarity with cloud-based data warehouses like Snowflake, and relational databases using SQL.
• Hands-on experience with deep learning, latent variable models (LVMs), and their applications to time-series monitoring, anomaly detection, and automated root cause analysis.
• Experience building or integrating LLMs into real-time decision support systems or user-facing agentic applications using Model Context Protocols and Agent2Agent frameworks.
• Proficiency in data visualization and real-time dashboard tools such as Streamlit, ReAct and Plotly.