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Data Scientist - Time Series Forecasting at ExxonMobil. ExxonMobil aims to lead in energy innovations that advance modern living and a net-zero future. We are one of the world’s largest publicly traded energy and chemical companies, powered by a diverse workforce focused on practical solutions in energy, chemicals, lubricants and lower-emissions technologies. In Malaysia, we host a global business and technology center in Kuala Lumpur providing IT and engineering expertise to ExxonMobil’s upstream, downstream and chemical businesses worldwide.

We seek key players to tackle and lead challenging commercial problems in supply demand, commercial, 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.

What role you will play in the team

• You will be part of our exciting and rapidly expanding Kuala Lumpur Modeling, Optimization & Data Science team, collaborating on a global scale to provide deep technical insights and support to ExxonMobil’s Product Solution Business and supply chain/commercial activities.
• 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.
• Position is based in Kuala Lumpur and not limited to Malaysia.
• Develop, deploy and act as the single point of contact for specific data science problems across multiple domains, technology support, uptake and value generation.
• Develop and evaluate new models using time series forecasting techniques using Python and/or integrating 3rd party tools with ExxonMobil data/platforms.
• Support development and execution of AI strategy consistent with the overall discipline vision and ensure alignment with business objectives.
• Assist in developing and delivering technical training content.
• Understand technology sustainment workflow and enhancements requests and develop new model/features and testing plans.

• Demonstrate industry leadership at conferences or via publications/patents (when applicable).
• Develop level of expertise in specific technical discipline to be recognized as a future leading global expert.
• Support discovery, development and deployment activities for the focused technology area consistent with the Technology Portfolio strategic vision and business partner goals.
• Proactively engages with Principal Engineers to deploy technology within their specific technical discipline, consistent with site needs/opportunities.
• Develop, deploy and act as the single point of contact for specific data science problems across multiple domains, technology support, uptake and value generation.
• Develop and evaluate new models using time series forecasting techniques using Python and/or integrating 3rd party tools with EM data/platforms.
• Support development and execution of AI strategy consistent with the overall discipline vision and ensure alignment with business objectives.
• Assist in developing and delivering technical training content.
• Understand technology sustainment workflow and enhancements requests and develop new model/features and testing plans.

Skills and Qualifications

• PhD degree in Data Science, Computer Science, IT, Applied Mathematics, Statistics, Engineering, or related disciplines with a minimum GPA of 3.5 (out of 4.0).
• At least 3 years of experience in time series forecasting, including research with publications, academics or industrial collaboration related to forecasting use cases.
• Experience in developing, applying, and validating data-driven tools to model complex systems.
• 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).
• Conceptual and mathematical understanding of algorithms, models, model assessment techniques, solution development and explainable AI.
• Proficiency in Python, including packages such as NumPy, pandas, scikit-learn, Keras, TensorFlow, and PyTorch.
• Familiarity with software testing and development practices (Agile).

• Supply chain, trading or commercial experience encompassing pricing, demand forecasting, and end-to-end value chain optimization are preferred.
• Prior experience in software development or working in software teams.
• Strong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.
• Excellent problem-solving skills and attention to detail.

We are committed to providing benefits that are competitive and support the needs of our employees.

Please be informed that only shortlisted candidates will be notified. You can learn more about our hiring process in this document.

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We thank you for your interest in ExxonMobil.

ExxonMobil is an Equal Opportunity Employer. All qualified applicants will be duly considered for employment.

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