Advanced Data Scientist

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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 can
work together .

We are seeking candidates to tackle and lead challenging commercial problems in pricing, marketing, sales, transportation, storage, and distribution of hydrocarbons. The ideal candidate will understand both the commercial/economic and technical aspects of the oil and gas sector and will be able to formulate and solve oil and gas industry problems using machine learning, time series forecasting, statistical analysis, and programming skills.

• Collaborate with data scientists, data analysts, software developers, and business representatives from chemical, lubricants, and fuels value chains globally to develop, deliver, and apply data-driven tools, models, or software to support our businesses.
• Utilize machine learning, time series analysis, pattern recognition, statistical analysis, design of experiments, and data visualizations, along with domain knowledge, to solve commercial problems and provide business insights.
• Design, build, and execute studies using proprietary or commercial tools to provide insights, including calibrating models to pricing/sales/demand data and providing optimized recommendations.

Skills and Qualifications

• Master’s, or PhD degree from a recognized university in Data Science, Computer Science, IT, Applied Mathematics, Statistics, Engineering, or related disciplines with a minimum GPA of 7.0 (out of 10.0).
• At least 5 years of experience in developing, applying, and validating data-driven tools to model complex systems.
• 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, validation methods).
• Practical experience in the full machine learning lifecycle, from problem formulation and data acquisition to model building and deployment at enterprise scale.
• Deep conceptual and mathematical understanding of algorithms, models, model assessment techniques, solution development and explainable AI.
• Extensive knowledge and experience in code design, testing, and ML Ops practices.
• Specialization in at least one sub-domain, such as time series forecasting, Bayesian skills or NLP-GenAI.
• Proficiency in Python, including packages such as Num Py, pandas, scikit-learn, Keras, Tensor Flow, and PyTorch.
• Experience with software engineering practices, agile methodologies, Dev Ops, and version control.
• Experience working with Azure Databricks or other data science frameworks.
• Familiarity with software testing and development practices (Agile).
• Experience with data visualization tools (e.g., Tableau, Power BI).

• Commercial experience encompassing pricing, demand forecasting, and end-to-end value chain optimization are preferred.
• Prior experience in commercial software development or working in commercial software teams.
• Ability to identify and scope data science opportunities based on business needs.
• Strong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.
• Excellent problem-solving skills and attention to detail.

An Exxon Mobil career is one designed to last.

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