Computational Scientist

Exxon Mobil Corporation; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Benefits offered by this job

Competitive pay

Medical and life benefits

Global networking opportunities

Annual vacations and holidays

Day care assistance program

Training and tuition support

Workplace flexibility policy

Relocation program

Transportation facility

Job summary

ExxonMobil is seeking a highly skilled researcher to develop hybrid models that blend chemistry-based insight with machine learning to accelerate product development in Bengaluru. The role involves analyzing lab and field data to connect formulation and processing with performance, and building predictive models for optimization and quality improvements.

You will design DOE studies, validate models, and translate complex results into actionable guidance for formulation strategy, working closely

Qualifications

• PhD or Master’s degree in Chemical Engineering, Materials Science, Mechanical Engineering, Data Science, or related field.
• Master’s candidates require 3+ years of industry experience; downstream/chemical/materials development preferred.
• Experience in formulation modeling or property prediction and hybrid modeling is desirable.

Responsibilities

• Develop and apply hybrid models that combine first-principles with data-driven methods to accelerate product development.
• Analyze experimental and field data to relate formulation, processing, and product performance.
• Build predictive models for formulation optimization, performance prediction, and quality improvement.
• Design and support DOE experiments to generate data for model development and validation.
• Collaborate with R&D scientists and product developers to guide formulation strategies.

Skills

Hybrid modeling

ML & statistics

Python

Time-series analysis

Experiment design

DOE

Education

PhD in Chemical Engineering

Master's in Chemical Engineering

Data Science

Materials Science

Tools

SQL

Databricks

Azure

AWS

Snowflake

Job description

• 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

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
• 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.

ExxonMobil is an Equal Opportunity Employer:

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status.