Data Scientist - Materials Characterization, Analytical Sciences & AI Agents

Eurofins EAG Laboratories is seeking a Data Scientist to advance data-driven analysis, intelligent automation, and AI-enabled decision support across materials characterization and analytical testing services.This role applies data science, statistics, machine learning, and AI agent development to complex, multi-modal laboratory data. The Data Scientist will design and deploy AI agents capable of automating data analysis workflows, orchestrating multi-step scientific reasoning, and accelerating insight generation.The role partners closely with scientists, engineers, and operational teams to enhance data quality, scalability, automation, and analytical capabilities in support of client-driven testing services.Essential Job FunctionsApply data science, machine learning, and AI methods to analyze and interpret materials characterization data across microscopy, spectroscopy, diffraction, and related techniques.Design, build, and deploy AI agents that automate data analysis tasks, including data ingestion, preprocessing, feature extraction, model selection, and report generation.Develop and maintain scalable data workflows, pipelines, and agent-based systems that improve efficiency, reproducibility, and throughput of laboratory data processing.Implement agent-driven orchestration of multi-step analytical workflows, enabling autonomous or semi-autonomous execution of scientific data analysis.Perform statistical analysis, feature engineering, and exploratory data analysis to identify trends, anomalies, and correlations in experimental datasets.Build, validate, and document predictive and classification models for materials characterization, failure analysis, and process optimization.Collaborate with scientists and engineers to translate experimental challenges into AI-augmented and agent-enabled solutions.Support automation and standardization of data collection, processing, and reporting using both traditional pipelines and intelligent agents.Communicate analytical insights and AI-driven results clearly to technical and non-technical stakeholders.Contribute to continuous improvement of data infrastructure, AI capabilities, and advanced analytics platforms.