About us

At Exxon Mobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.

We invite you to bring your ideas to Exxon Mobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we canwork** together**.

What role you will play in our team

As a Data Scientist, you will drive end to end data science and AI solutions to solve complex oil and gas challenges. You will apply advanced machine learning, statistical modeling, and programming across diverse domains including Generative AI & NLP, time‑series forecasting, commercial analytics and computer vision. The role involves working closely with engineers and business stakeholders, and delivery of scalable and production ready solutions starting from problem scoping and experimentation through deployment and sustainment.

What will you do

• Work with data scientists, data analysts, computational engineers, machine learning engineers, software developers, or business representatives across our global organization to research, develop, and deliver data science tools, models, or software for solving challenging business problems in the oil and gas industry.

• Lead end-to-end delivery of AI/ML solutions: scoping, modeling, evaluation, deployment, and monitoring.

• Develop GenAI/NLP applications, and/or time-series, computer vision, commercial analytics models.

• Build production-ready solutions applying MLOps best practices (MLflow, CI/CD, monitoring, data quality).

• Apply data science methods, machine learning tools, visualization and/or statistical techniques along with domain knowledge to generate actionable insights and provide optimized recommendations.

About You

• Skills and Qualifications

• Expertise in one or more of the following: Time Series Analysis, Computer Vision, Natural Language Processing, Generative AI, Commercial Analytics.

• Master’s or Ph.D. degree from a recognized university in one of the following disciplines: Data Science, Computer Science, IT, Chemical Engineering, Mechanical, Civil, Materials, Aerospace, Geoscience/Geophysics, Applied Math or related disciplines with a minimum GPA of 7.0.

• 5+ years of relevant experience in developing, delivering, and validating production-ready AI/ML solutions.

• In-depth knowledge and practical experience in statistical analysis techniques (e.g., classification, regression, time-series, Bayesian techniques) and machine learning techniques (e.g., decision trees, ensemble methods, deep learning, neural networks, causal analysis).

• Practical experience in the full machine learning lifecycle from problem formulation, data acquisition, data cleaning to model building and deployment at enterprise level.

Proficiency in Python or R, ML frameworks (Py Torch, Tensor Flow, scikit-learn) and libraries (Num Py, pandas).

• Experience with software engineering practices, agile methodologies and version control (Git).

• Strong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.

Key Skills:

• Applied Data Science

• Statistical Modeling & Analysis

• Machine Learning & Deep Learning

• Generative AI, NLP, Computer Vision

• Time Series Analysis & Forecasting

• End‑to‑End ML Project Lifecycle

• Python/R Programming Skills

• Software Engineering & Agile Framework

Preferred Experience

• Excellent problem-solving skill and attention to detail.

• Prior experience with oil & gas, commercial domain, supply chain, production systems, wells or subsurface domain is highly desirable.

• Experience working with Azure Databricks or other data science frameworks.

• Experience with mathematical modeling, physics-based simulators, scientific computing and numerical methods would be an added advantage.

Your benefits

An Exxon Mobil 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.

Stay connected with us

• Learn more about Exxon Mobil in India, visit Exxon Mobil India and Energy Factor India.

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EEO Statement

Exxon Mobil 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.

Business solicitation and recruiting scams

Exxon Mobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of Exxon Mobil.

Alternate Location:

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 Exxon Mobil, 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, Exxon Mobil 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.