Pharma Data Engineer: ML, LLM & IIoT Innovator

Pauwels Consulting; Geel; Hybride; EUR 70 000 - 105 000; Plein temps

Résumé du poste

Pauwels Consulting in Geel is seeking a data science professional to drive digital transformation in a high-tech production environment. You will develop advanced data solutions, including ML and AI, to optimize manufacturing quality and efficiency.

Responsibilities include collecting production data, building data pipelines in Python/SQL, designing ML models for time-series, and deploying LLM apps for document processing. Collaboration across teams and GMP-compliant documentation are required.

Qualifications

• 3+ years in data science or analytical roles.
• Strong Python for data analysis and automation (pandas, scikit-learn, NumPy).
• SQL expertise for relational DB and complex queries.
• Experience building/validating ML models for time-series and predictive analysis.
• Knowledge of LLMs, fine-tuning and prompt engineering.
• IIoT data contextualization using AVEVA PI AF or Seeq.
• Master’s or Bachelor’s in Data Science/CS/Engineering.

Responsabilités

• Collect and process production data from historians, MES, and sensors.
• Develop data pipelines and analytics in Python and SQL.
• Design ML models for predictive maintenance and anomaly detection.
• Implement LLM applications for document processing and knowledge extraction.
• Collaborate with cross-functional teams to translate digital solutions into value.
• Document methodologies and results per GMP requirements.

Connaissances

Python

SQL

Machine Learning

LLM

Prompt engineering

IIoT data

Dutch

English

3+ years exp

Formation

Master's or Bachelor's degree in Data Science/CS/Engineering

Outils

AVEVA PI Asset Framework

Seeq

DeltaV DCS

Cursor

Claude

Description du poste

Pauwels Consulting in Geel is seeking a data science professional to drive digital transformation in a high-tech production environment. You will develop advanced data solutions, including ML and AI, to optimize manufacturing quality and efficiency.

Responsibilities include collecting production data, building data pipelines in Python/SQL, designing ML models for time-series, and deploying LLM apps for document processing. Collaboration across teams and GMP-compliant documentation are required.