What You Will Do - Develop and apply hybrid models that combine first-principles understanding (chemistry, materials behavior) with data-driven methods to accelerate product development.
- Analyze experimental and field data to uncover relationships between formulation, processing conditions, and product performance.
- Build predictive models to support:
- Formulation optimization
- Performance prediction
- Product stability and robustness
- Quality improvement
- Design and support experiments (DOE) to efficiently generate data for model development and validation.
- Collaborate closely with R&D scientists, chemists, and product developers to guide formulation strategies and decision-making.
- Develop data-driven insights and digital tools to reduce development cycle time and improve success rates.
- Ensure model validity through proper validation, uncertainty quantification, and alignment with domain knowledge.
- Document methodologies, assumptions, and modeling workflows to support reproducibility and knowledge sharing.
- Contribute to development of reusable modeling frameworks and best practices for data-driven product innovation.
About You - Strong foundation in hybrid modeling, integrating domain knowledge (chemistry, formulations, materials behavior) with statistical and machine learning approaches.
- Experience applying modeling to product development, formulation optimization, and performance prediction.
- Solid understanding of experimental data (lab, pilot, and field) and how to incorporate it into predictive models.
- Proficiency in Python or other programing languagesfor data analysis, modeling, and automation.
- Experience with time-series and experimental datasets related to product performance, stability, and quality.
- Demonstrated ability to translate complex modeling results into insights that guide product design and development decisions.
- Strong communication skills and ability to collaborate with scientists, chemists, and product developers.
- Familiarity with SQL and modern data platforms (Databricks, Azure, AWS, Snowflake) is a plus.
- Ability to work independently and within cross-functional R&D teams.
Skills/Qualifications - PhD or Master's degree in Chemical Engineering, Materials Science, Mechanical Engineering, Data Science, or a related field.
- For Master's candidates, minimum 3+ years of industry experience required; experience in downstream, chemical, or materials/product development environments is strongly preferred.
- Strong preference for candidates with experience in:
- Formulation modeling or property prediction
- Hybrid modeling applied to product or material performance
Your Benefits An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you:
- Competitive compensation
- Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits
- Retirement benefits
- Global networking & cross-functional opportunities
- Annual vacations & holidays
- Day care assistance program
- Training and development program
- Tuition assistance program
- Workplace flexibility policy
- Relocation program
- Transportation facility
Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company's eligibility guidelines.
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