Senior Advanced R&D Engineer, Scientist

. Analyze complex experimental, analytical, and manufacturing datasets using statistical and machine learning methods .

Posted 9/25/2026full-timeUnited StatesSenior💰 $146,976 - $183,425 per yearWebsite

Tools & technologies

NoSQLPythonSQLTableau

Key responsibilities & impact

Analyze complex experimental, analytical, and manufacturing datasets using statistical and machine learning methods
Develop and validate predictive models to improve material performance, evaluate key variables, and support product and process development
Partner with chemists, materials scientists, engineers, and business stakeholders to define data needs and develop analytical solutions
Evaluate and implement state-of-the-art data science methods for advanced materials applications
Design, build, and maintain scalable data pipelines and databases for experimental and analytical data
Establish data quality practices ensuring reliable, traceable, and reproducible datasets and analyses
Communicate findings, recommendations, and technical limitations through visualizations, reports, and presentations
Report directly to the R&D Manager

What you’ll need

Master’s or Ph.D. in Data Science, Materials Science, Statistics, Applied Mathematics, or a related field
Minimum of 5 years of experience in data analysis or data science roles within a materials science or engineering domain
Proficiency in programming languages such as Python
Familiarity with data manipulation libraries relevant to chemistry and materials, such as RDKit
Experience developing physics-informed neural networks, surrogate models, cheminformatics models, or quantitative structure–property relationship models
Strong understanding of statistical modeling, machine learning algorithms, and data visualization techniques
Experience with data visualization tools or packages such as Tableau, Power BI, Origin, matplotlib, or seaborn
Experience with databases such as SQL or NoSQL
Deep knowledge of advanced materials, including polymers, nanomaterials, ceramics, metals, small molecules, formulations, or composites
Familiarity with experimental methods in materials characterization and testing
Familiarity with chemical manufacturing processes, process modeling, and process optimization
Excellent problem-solving abilities and critical thinking skills
Strong interpersonal and communication skills, capable of engaging with technical and non-technical audiences
Ability to work independently and manage multiple projects simultaneously in a fast-paced environment
Commitment to continuous learning in data science and materials science

Comp & perks