Artificial Intelligence Scientist

Exxon Mobil Corporation; Bengaluru; On-site; INR 1,500,000 - 2,700,000; Full time

Benefits offered by this job

Competitive compensation

Medical plans and benefits

Global networking & cross-functionalOp

Annual vacations & holidays

Training and development program

Tuition assistance program

Relocation program

Job summary

Exxon Mobil Corporation in Bengaluru seeks a statistics-focused professional to apply rigorous methods to large datasets, design DOE experiments, and develop robust models. You will translate complex results into actionable insights for cross-functional teams and contribute to reproducible analytics across operational platforms.

You will work with tools like SQL, Databricks, and Power BI/Tableau, communicating findings clearly to technical and non-technical stakeholders while advancing

Qualifications

• PhD or MSc in Statistics or closely related quantitative field.
• 3+ years of industry experience for Master’s candidates; chemical/manufacturing experience is a plus.
• Hands-on experience in experimental design, causal inference, and statistical modeling in real-world industrial settings.
• Balance statistical rigor with practical business impact.

Responsibilities

• Apply rigorous statistical methods to analyze high-volume datasets and extract insights.
• Design and execute experiments (DOE) to support product development and process optimization.
• Develop, validate, and maintain statistical models with diagnostics and interpretable outputs.
• Collaborate with engineers, scientists, and stakeholders to frame problems statistically and guide data-driven decisions.
• Create dashboards and analytical tools communicating variability, uncertainty, and KPIs effectively.
• Ensure reproducibility through documentation, version control, and best practices.
• Contribute to standardized statistical methodologies and reusable code libraries.
• Integrate statistical analysis into operational and digital platforms where appropriate.

Skills

Statistical inference

Regression modeling

Experimental design (DOE)

Multivariate methods

R

Python

Data wrangling

Communication of results

Education

PhD or MSc in Statistics / Biostatistics / Applied Mathematics

Tools

Power BI

Tableau

SQL

Databricks

Azure

AWS

Snowflake

Job description

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• Apply rigorous statistical methods to analyze complex, high-volume datasets and extract meaningful insights.
• Design and execute experiments (e.g., DOE, hypothesis testing frameworks) to support product development, process optimization, and quality improvement.
• Develop, validate, and maintain statistical models, ensuring proper assumptions, diagnostics, and interpretability.
• Partner with engineers, scientists, and other stakeholders to frame problems statistically and guide data-driven decisions.
• Create dashboards and analytical tools that communicate variability, uncertainty, and key performance metrics effectively.
• Ensure reproducibility and robustness of analyses through proper documentation, version control, and statistical best practices.
• Contribute to the development of standardized statistical methodologies, reusable code libraries, and analytical workflows.
• Integrate statistical analysis into operational and digital platforms where appropriate.

About You

• Deep expertise in statistical inference, regression modeling, experimental design (DOE), and multivariate methods.
• Strong programming skills in R or Python, with emphasis on statistical computing, reproducible analysis, and data wrangling.
• Proven ability to translate complex statistical results into clear, actionable insights for both technical and non-technical stakeholders.
• Strong communication skills, including presenting statistical findings, assumptions, and limitations in industrial research setting.
• Experience designing, analyzing, and interpreting experiments (e.g., A/B testing, process optimization studies).
• Familiarity with data visualization and reporting tools (e.g., Power BI, Tableau).
• Working knowledge of SQL and modern data environments (e.g., Databricks, Azure, AWS, Snowflake) is a plus.
• Ability to work independently and collaboratively within cross-functional teams.

Skills/Qualifications

• PhD or Master’s degree in Statistics, Biostatistics, Applied Mathematics, or a closely related quantitative field (Data Science or Engineering considered with strong statistical emphasis).
• For Master’s candidates, a minimum of 3+ years of industry experience is required; experience in chemical, manufacturing, or process industries is a plus.
• Candidates with hands‑on experience in experimental design, causal inference, and statistical modeling in real‑world industrial settings.
• Candidates with a demonstrated ability to balance statistical rigor with practical business impact are especially encouraged to apply.

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.

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

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