Manufacturing Data Scientist (Code: 2993906)
this position
Permanent (Full-Time) Limerick/Hybrid Hybrid
Company Information and Introduction
About Digital Manufacturing Ireland (DMI)
Digital Manufacturing Ireland (DMI) is an industry-led organisation, supported by the Government of Ireland through IDA Ireland. Launched in 2023, DMI enables Irish-based manufacturers to access, adopt, and accelerate new digital technologies—solving real-world challenges and driving future competitiveness.
DMI offers a state-of-the-art physical and digital factory, a vendor showcase, industry collaboration spaces, and training facilities. The DMI facility brings together technology, expertise, and business support to help manufacturing companies transform, innovate, and future-proof their operations.
Key Responsibilities and Duties
Apply ML models to optimize manufacturing processes.
Identify and define high-impact manufacturing use cases that solve operational problems.
Translate shop-floor challenges into structured data and technology solutions.
Develop business cases for manufacturing technology implementations.
Support configuration and optimisation of manufacturing systems
Deep understanding of manufacturing and supply chain processes
Partner with commercial team to provide technical subject matter expertise during workshops and client pitches.
Support client conversations with a solution mindset, balancing technical constraints with business needs.
Technical Capabilities
Strong Python proficiency (pandas, scikit-learn, PyTorch/TensorFlow etc).
Time-series modelling and anomaly detection.
Statistical process control.
SQL and industrial data pipelines.
Familiarity with OT/IT integration (OPC UA, SCADA, PLC ingestion).
Understanding of feature engineering and reusable industrial data assets
Exposure to model monitoring, drift detection, and lifecycle management
Key Skills and Competencies
Minimum 3+ years' experience in a manufacturing environment.
Experience in Life Sciences, Pharma, MedTech, or Biotech; strongly preferred.
Experience working with MES, historians, PLC data, and shop-floor systems.
Experience in predictive maintenance, anomaly detection, quality analytics, or production optimisation.
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