Data Scientist, Materials Analysis

Eurofins EAG Laboratories is seeking a Data Scientist to support and advance data-driven analysis across our materials characterization and analytical testing services with an emphasis on TEM (Transmission Electron Microscopy). This role applies data science statistics and machine learning to complex multi-modal laboratory data generated from a broad range of analytical techniques.

The Data Scientist partners closely with scientists engineers and operational teams to improve data quality automation insight generation and analytical capabilities in support of client-driven testing services. 

Essential Job Functions: 

• Responsible for building algorithms and developing software to automate the TEM data collection and processing using computer science techniques (computer vision machine learning etc.).
• Apply data science and machine learning methods to analyze model and interpret materials characterization data across multiple analytical techniques including microscopy spectroscopy diffraction and other physical or chemical testing methods. 
• Support the data process from various materials characterization techniques including TEM SEM EDS XRD XPS and RBS.
• Develop and tune TEM automation on cutting edge TEM microscopes. 
• Perform image processing - including image enhancement segmentation measurement and visualization on 2D and 3D data sets.  
• Proactive in developing new TEM technologies (such as 4D STEM) to meet new demands from customers. 
• Collect S/TEM EDS/EELS data and prepare reports per instructions. 
• Support TEM jobs including S/TEM EDS/EELS. 
• Develop and maintain data analysis workflows and pipelines that improve efficiency reproducibility and scalability of laboratory data processing. 
• Perform statistical analysis feature extraction and exploratory data analysis to identify trends anomalies and correlations in experimental data. 
• Build validate and document predictive or classification models to support materials characterization failure analysis process optimization and customer reporting. 
• Collaborate with laboratory scientists and engineers to translate experimental and customer questions into data-driven solutions. 
• Support automation and standardization of data collection processing and reporting where appropriate. 
• Communicate analytical results clearly to technical and non-technical stakeholders. 
• Contribute to continuous improvement initiatives related to analytical capabilities data infrastructure and quality systems. 

Supervisory Responsibilities:  This position has no direct supervisory responsibilities. 

Thisposition works with companies that deal with defense-related activities and is subject toITAR(International Traffic in Arms Regulations).

All considered applicants must be U.S. Persons as defined by ITAR: U.S. Citizen U.S. Permanent Resident (i.e. Green Card Holder) or Political Asylee or Refuge.

Qualifications :

Job Requirements: 

• MS or PhD in Materials Science Data Science Engineering Physics Chemistry or a related field or equivalent applied experience. 
• Strong background in TEM principles operation of S/TEM EDS/EELS and automation. 
• Demonstrated experience applying data science or statistical methods in a laboratory engineering or applied science environment. 
• Proficiency in Python and common scientific data analysis libraries (e.g. NumPy Pandas SciPy scikit-learn). 
• Experience working with experimental sensor image spectral or time-series data. 
• Strong written and verbal communication skills. 

Job Knowledge Skills and Ability: 

• Strong foundation in statistics data analysis and applied machine learning. 
• Ability to evaluate model performance and understand limitations of scientific datasets. 
• Familiarity with machine learning frameworks such as PyTorch or TensorFlow for applied use cases. 
• Experience with data visualization and scientific reporting. 
• Ability to work collaboratively in a fast-paced client-focused analytical services environment. 

Preferred: Advanced Machine Learning & Modeling 

• Experience applying advanced machine learning techniques such as deep learning or representation learning to scientific datasets. 
• Familiarity with image spectral time-series or multi-modal data modeling. 
• Exposure to modern neural network architectures (e.g. CNNs RNNs transformers) and understanding when advanced methods are appropriate. 
• Knowledge of signal processing or feature extraction techniques used in scientific instrumentation data. 
• Familiarity with model lifecycle practices such as experiment tracking versioning and reproducibility. 

Physical Requirements:

• Ability to continuously operate a personal computer or lab equipment for extended periods of time (4 or more hours).
• Ability to operate a keyboard and other lab equipment use a telephone access file cabinets and other items stored at various levels including overhead.   
• Must be able to remain in a stationary position 80% of the time. 
• Ability to communicate clearly and understandably ensure an accurate exchange of information in normal conversational distance over the telephone and in a group setting.
• Ability to handle small and fragile devices with tweezers and /or fingers.
• Require close distance visual acuity with or without correction (Glasses Contacts etc.)
• Must be willing and able to wear PPE such as hard-hat steel-toed shoes safety glasses laboratory coat and/or any other devices or equipment that is required. 
• Learn new tasks remember processes maintain focus complete tasks independently make timely decisions in the context of a workflow ability to communicate with visitors ability to complete tasks in situations that have a speed or productivity quota. 
• Ability to move equipment or items up to 50 lbs. 

The essential physical and mental requirements described here are representative of those that must be met by an employee to successfully perform the essential functions of the job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.   

We will consider reasonable accommodations for qualified individuals with disabilities. If you have a disability or special need we would like to know how we can better accommodate you.   

Additional Information :

Compensation is aligned with market standards for the region and tailored to individual qualifications and experience.

Why Join Us 

At EAG Laboratories we value innovation collaboration and professional growth. You will have the opportunity to work with a team of experts in a dynamic and supportive environment. We offer competitive compensation comprehensive benefits and opportunities for career advancement.

What Its Like to Work Here:

• Teamwork: Be inspired by your leaders be encouraged by your teammates and be supported in all parts of your journey while you work with us.
• Learning & Development: Take on career development programs and goal setting to create big possibilities for your career and life. Develop within the company; be mentored and grown as a leader.
• Diversity & Authenticity: We work hard to embrace diversity and inclusion and encourage everyone to bring their authentic selves to work every day.

Benefits & Perks to Foster Work/Life Balance:

401k Company Matching

Wellness Program

Volunteer Time off

Education Assistance

Fitness Reimbursement

and more!

Eurofins EAG Laboratories is committed to promoting an equal employment opportunity workplace environment and is an equal opportunity employer. It is the policy of the Company that all qualified applicants will receive consideration for employment without regard to race color religion sex age national origin citizenship pregnancy genetic information (GINA) disability military and/or veteran status and/or any other status protected by applicable Federal state or local law.  The Companys policy is to recruit hire train promote and administer all employment-related matters based on an individuals qualifications abilities and efforts without regard to protected status. 

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Eurofins USA Material Sciences is a Disabled and Veteran Equal Employment Opportunity employer.

Remote Work :

No

Employment Type :

Full-time