Data Scientist, Materials Characterization
About The Position
Eurofins EAG Laboratories is hiring a Data Scientist to improve scientific data analysis, workflow automation, and AI-supported decision-making across our materials characterization and analytical testing services. This role is not a general business analytics or software-only data science role. Candidates should have experience applying data science or machine learning to scientific, laboratory, engineering, or experimental data and have had experience operating and performing analysis using materials characterization instrumentation. This role is best suited for someone who has applied data science in a laboratory, engineering, or scientific environment and can work with complex datasets such as spectral, image, surface, sensor, or time-series data. The Data Scientist will build practical tools and workflows that improve data quality, analysis speed, and reporting in a production lab setting.
Requirements
- A Degree in Data Science or Computer Science AND MS or PhD in Materials Science, Engineering, Physics, Chemistry or related field
- Hands-on experience applying data science or machine learning in a scientific, laboratory, manufacturing, or engineering environment
- Strong Python skills (NumPy, Pandas, SciPy, scikit-learn)
- Experience working with experimental, spectral, image, sensor, or time-series data
- Experience analyzing data generated from materials characterization instrumentation
- Experience building data workflows, automation tools, or applied AI solutions
- Strong written and verbal communication skills
- Authorized to access export-controlled information under U.S. law (U.S. citizens, U.S. lawful permanent residents, individuals granted asylum or refugee status in the United States)
Nice To Haves
- Experience with materials characterization techniques (e.g., XPS, AES, SIMS, microscopy, spectroscopy)
- Familiarity with spectroscopy workflows (peak fitting, quantification, chemical state analysis)
- Experience with PyTorch, TensorFlow, or similar frameworks
- Experience with multimodal scientific datasets
- Experience developing or integrating AI-enabled workflow tools, including LLM-based systems
- Familiarity with signal processing, spectral analysis, or feature extraction
- Experience in analytical services, failure analysis, or process optimization environments
Responsibilities
- Analyze complex scientific data using statistics, machine learning, and data science methods
- Build and improve workflows for data ingestion, cleaning, feature extraction, modeling, and reporting
- Develop AI-enabled tools or workflow automation to support repeatable scientific analysis tasks
- Partner with scientists, engineers, and operations teams to solve practical lab data problems
- Build, test, validate, and document predictive or classification models for scientific applications
- Perform exploratory analysis to identify trends, anomalies, and relationships in experimental data
- Support automation and standardization of data analysis and reporting processes
- Communicate results clearly to both technical and non-technical stakeholders
- Contribute to scalable, reproducible data workflows that improve lab efficiency
Benefits
- 401k Company Matching
- Wellness Program
- Volunteer Time off
- Education Assistance
- Fitness Reimbursement
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What This Job Offers
Job Type
Full-time
Career Level
Senior
