Advanced Data Scientist

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

Job summary

A leading energy company in Bengaluru seeks an experienced data scientist to develop AI/ML solutions and deliver data science tools for the oil and gas industry. Ideal candidates will have 5+ years of relevant experience and advanced skills in data science methods such as Time Series Analysis and Natural Language Processing. A Master’s or Ph.D. in a relevant discipline is required. Strong Python or R programming skills are essential, along with proficiency in machine learning frameworks and communication skills for teamwork.

Qualifications

• 5+ years of relevant experience in developing AI/ML solutions.
• Expertise in one or more: Time Series Analysis, NLP, Generative AI.
• Practical experience in full ML lifecycle from problem formulation to deployment.

Responsibilities

• Lead end-to-end delivery of AI/ML solutions: scoping to monitoring.
• Develop GenAI/NLP applications and time-series analysis models.
• Build production-ready solutions applying MLOps best practices.

Skills

Applied Data Science

Statistical Modelling & Analysis

Generative AI, NLP, Computer Vision

Time Series Analysis & Forecasting

Python/R Programming Skills

Software Engineering & Agile Framework

Education

Master’s or Ph.D. in Data Science or related fields

Tools

Python

R

PyTorch

TensorFlow

scikit-learn

Azure Databricks

Job description

Company: ExxonMobil Services & Technology Private Limited

About us

At ExxonMobil, 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 optimise our strategy in energy, chemicals, lubricants and lower‑emissions technologies.

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs.

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, modelling, 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, visualisation and/or statistical techniques along with domain knowledge to generate actionable insights and provide optimised 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 recognised 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 (PyTorch, TensorFlow, scikit‑learn) and libraries (NumPy, 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 Modelling & Analysis
• Generative AI, NLP, Computer Vision
• Time Series Analysis & Forecasting
• 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 modelling, physics‑based simulators, scientific computing and numerical methods would be an added advantage.

Functional Skills

• Applied Software Engineering for Data
• Mathematical Framing of Business Problems