Data Scientist - Materials Characterization, Analytical Sciences & AI Agents

Company Description

Eurofins EAG Laboratories has almost 50 years of experience in engineering and materials testing services. Our parent company, Eurofins Scientific, is a multi-billion-dollar global leader in engineering and scientific services, operating over 950 labs in 60 countries with 65,000 employees and a portfolio of over 200,000 validated analytical methods.

At EAG, curiosity fuels everything we do. Every analysis, every test, and every question asked in our labs helps unlock what materials and products are capable of—and what the world can build next. If you’re energized by materials science, analytical chemistry, engineering rigor, and solving problems that matter, you’ll feel right at home here.

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. The role applies data science, statistics, machine learning, and AI agent development to complex, multi‑modal laboratory data, driving the design and deployment of AI agents that automate data analysis workflows, orchestrate multi‑step scientific reasoning, and accelerate insight generation.

The Data Scientist will partner with scientists, engineers, and operations to strengthen data quality, automation, and analytics for client testing work. Strong candidates should have experience working with materials characterization data (e.g., XPS and other spectral/surface datasets) and understand spectroscopy workflows such as peak fitting, quantification, and chemical state analysis.

This position works with companies that deal with defense‑related activities and is subject to ITAR (International Traffic in Arms Regulations). All considered applicants must be U.S. Persons as defined by ITAR: U.S. Citizen, U.S. Permanent Resident (Green Card Holder), or Political Asylee or Refugee.

• Apply 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.

• MS or PhD in Materials Science, Data Science, Engineering, Physics, Chemistry, Applied Mathematics, or related field.
• Demonstrated experience applying data science, machine learning, or statistical methods in laboratory or engineering environments.
• Proficiency in Python and scientific computing libraries (Num Py, Pandas, Sci Py, scikit‑learn).
• Experience working with experimental, image, spectral, sensor, or time‑series data.
• Experience developing or integrating AI agents, automation frameworks, or LLM‑based systems for data analysis or workflow automation (e.g., Lang Chain, semantic orchestration frameworks, or agent‑based architectures).
• Strong written and verbal communication skills.

• Strong…