H.B. Fuller is seeking a Materials Data Scientist to accelerate innovation and performance prediction of materials and formulations in chemistry, polymer science, and material science by designing and implementing predictive models and data-driven workflows.
Requirements
- Proven expertise in data science, including statistical modeling, predictive analytics, and machine learning
- Proficiency in Python or similar programming languages for data analysis and scientific computing.
- Strong analytical skills with the ability to transform experimental data into actionable insights.
- Familiarity with digital R&D platforms such as ELN, LIMS, PLM, or data lakes.
- Ensure digital systems such as ELNs, LIMS, PLM, and data lakes can share data in consistent formats, work together in real time, and allow seamless access and analysis.
- Apply best practices in data governance and structured data management.
- Utilize cloud-based systems, APIs, and scientific data infrastructure effectively.
Responsibilities
- Partner with R&D teams to design and implement predictive models and data-driven workflows for materials and formulation innovation.
- Manage, clean, transform, and integrate large datasets from experimental, formulation, and materials testing sources.
- Identify patterns, correlations, and performance drivers in materials systems through advanced analytics.
- Leverage machine learning and statistical methods to accelerate material selection, formulation optimization, cost, and performance prediction.
- Help build and execute a roadmap for R&D digital transformation, ensuring alignment with broader enterprise goals.
- Support digital adoption within R&D by training scientists on informatics tools and workflows.
- Develop robust, maintainable Python code (or equivalent) to automate data preparation, model training, and results visualization.
Other
- Advanced degree (Ph.D. or M.S.) in Chemistry, Polymer Science, Material Science, Chemical Engineering or a related field.
- 3+ years of relevant materials informatics/data science experience.
- Excellent communication skills and ability to collaborate across scientific and disciplines.
- Ability to travel up to 10% including internationally
- This position is not eligible for work visa sponsorship. Applicants must have U.S. work authorization that does not now or in the future require H.B. Fuller sponsorship of a work visa to work for H.B. Fuller.
