About usAt 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 optimize 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. Learn more about our What and our Why and how we can work together.What role you will play in our teamWe are looking to hire candidates to work on challenging engineering, geological and commercial problems that focus on exploration, development, production, marketing and transportation of hydrocarbons. A successful candidate would understand a problem in oil and gas space (both commercially/economically and technically), be able to formulate the problem in a solvable way, using application of engineering, numerical, data science and programming skills to tackle a range of problems in the oil and gas industryWhat you will do:Work with data scientists, computational scientists, engineers, software developers, and geoscientists across the globe to develop, deliver and apply computational tools, models, or software to support our business.:Use machine learning, pattern recognition, deep learning, statistical analysis and data visualizations : along with domain knowledge and subject:specific models (eg. physics:based) : to solve science, engineering, commercial problems and provide business insights.Design, build, and execute studies using proprietary or commercial tools to provide insights including calibrating models to field data and providing field optimization recommendations.About YouSkills and Qualifications:Bachelors degree from a recognized university in one of the following disciplines: Chemical Engineering, Mechanical Engineering or related disciplines with minimum GPA 7.0 (out of 10.0) and above:Minimum 3 years of work experience in developing, applying, and validating data:driven tools to model complex systems.:In:depth knowledge and practical experience in applying statistical analysis techniques, such as classification, regression, time:series, Bayesian techniques, etc. and machine learning techniques, such as decision:trees, ensemble methods, deep learning, neural networks, validation methods etc.:Practical experience in the full machine learning life cycle from problem formulation, data acquisition, modeling building, and deployment at enterprise scale.:Specialization in at least one of the sub:domains e.g. Natural Language Processing (NLP), Computer Vision, Time series forecasting, PINN's, causality analysis.:Experience in Python and R and related packages such as numpy, pandas, sklearn, Keras, Tensorflow, PyTorch:Experience with software engineering practices, agile methodologies, DevOps, version control:Experience working in Azure Databricks or any other data science frameworks:Software testing and development practices (Agile)Preferred Qualifications / Experience:Experience in developing, applying, and analyzing physics:based or data driven computational models and simulations is an advantage:Prior knowledge of commercial software development and/or experience in commercial software teams:Experience of identifying and scoping data science opportunities based on business needs is an advantage:Strong communication and interpersonal skillsYour benefitsAn ExxonMobil career is one designed to last. Our commitment to you runs deep our employees grow personally and profession