Data Scientist – Materials Characterization, Analytical Sciences, AI Agents

Eurofins

Data Scientist at Eurofins EAG Laboratories applying AI and data science methods to analyze materials characterization data. Collaborating with scientists and engineers for advanced data solutions.

Posted 6/5/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $115,000 - $180,000 per yearWebsite

Tech Stack

Tools & technologies

NumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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 (NumPy, Pandas, SciPy, 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., LangChain, semantic orchestration frameworks, or agent-based architectures).
Strong written and verbal communication skills.

Benefits

Comp & perks

401k Company Matching
Wellness Program
Volunteer Time off
Education Assistance
Fitness Reimbursement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningAI methodsstatistical analysisfeature engineeringpredictive modelsclassification modelsdata workflowsdata pipelinesautomation frameworks

Soft Skills

communication skillscollaborationproblem-solving

Certifications

MS in Materials SciencePhD in Data SciencePhD in EngineeringPhD in PhysicsPhD in ChemistryPhD in Applied Mathematics