Sr Advanced R&D Engr/Scientist

About the role

As a Sr Advanced R&D Engineer/Scientist here at Solstice, you will drive innovation, develop cutting-edge technologies, and lead advanced research initiatives to enhance aerospace safety, efficiency, and reliability. You will report directly to our Sr R&D Manager, and you’ll work out of our Spokane, WA location on a hybrid schedule. This position is available in Morris Plains, NJ, or Buffalo, NY.

Responsibilities

• Analyze complex experimental, analytical, and manufacturing datasets using statistical and machine learning methods to identify trends, patterns, and relationships.
• Develop and validate predictive models to improve material performance, evaluate the effects of key variables, and support product and process development.
• Partner with chemists, materials scientists, engineers, and business stakeholders to define data needs, develop analytical solutions, and influence decisions.
• Evaluate and implement state-of-the-art data science methods for advanced materials applications, informed by relevant scientific and technical literature.
• Design, build, and maintain scalable data pipelines and databases for experimental and analytical data.
• Establish data quality practices that ensure reliable, traceable, and reproducible datasets and analyses.
• Communicate findings, recommendations, and technical limitations through clear visualizations, reports, and presentations for technical and non-technical audiences.

Qualifications

• 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 and familiarity with data manipulation libraries relevant to chemistry and materials (e.g., 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 (e.g., Tableau, Power BI, Origin, matplotlib, seaborn) and databases (e.g., SQL, NoSQL).

Skills

• 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.

Benefits

In addition to a competitive salary, leading