Data Scientist - Time Series Forecasting
Kuala Lumpur, Federal Territory of Kuala Lumpur, MY, 50088
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDevelop and evaluate time series forecasting models using Python
Deploy data science solutions and act as single point of contact for specific problems
Work with Principal Engineers to implement technology within their discipline
Develop new model features and testing plans for sustainment requests
Support AI strategy and assist in delivering technical training content
From the employer’s posting
Develop and evaluate new models using Timeseries forecasting techniques using python
Develop, deploy and act as the single point of contact for specific data science problems across multiple domains
Proactively engages with Principal Engineers to deploy (implement) technology within their specific technical discipline
Understand technology sustainment workflow and enhancements requests and develop new model/features and testing plan.
Support development and execution of AI strategy consistent with the overall discipline vision
What you’ll bring
All qualificationsCore experience
- Experience in developing, applying, and validating data-driven tools to model complex systems.
- Prior experience in software development or working in software teams.
- 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).
- Strong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.
- Proficiency in Python, including packages such as NumPy, pandas, scikit-learn, Keras, TensorFlow, and PyTorch.
- Familiarity with software testing and development practices (Agile).
Qualification wording
Experience in developing, applying, and validating data-driven tools to model complex systems.
Prior experience in software development or working in software teams.
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).
Strong communication and interpersonal skills, with the ability to work collaboratively in a global team environment.
Proficiency in Python, including packages such as NumPy, pandas, scikit-learn, Keras, TensorFlow, and PyTorch.
Familiarity with software testing and development practices (Agile).
Education & alternatives
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 experiences of specialization in time series forecasting, in either research with publications, academics or industrial collaboration related to forecasting use cases
Tools in this posting
- Python
- Keras
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Source — Tool mentions in context
- 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 Timeseries 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
- 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).
About ExxonMobil
At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- May 21, 2026 · 150 days ago
- Recorded sightings
- 903
- Last seen by us
- Oct 18, 2026
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Your next step
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Job description
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 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.
ExxonMobil in Malaysia
In Malaysia, we host a global business and technology center in Kuala Lumpur that provides high-level information technology and engineering expertise to ExxonMobil’s Upstream, Product Solutions and Low Carbon Solutions businesses worldwide. In the upstream, we have interests in two Production Sharing Contracts with PETRONAS, while in the Product Solutions business, we supply a portfolio of specialty chemical products to the marketplace.
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 working and collaborating on a global scale providing deep technical insights and support to ExxonMobil’s Product Solution Business and supply chain/commercial activities
- As a key member of the team, you will 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.
- You will be part of the team utilizing 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 Malaysian.
What you will do
- Demonstrate industry leadership at conferences or via publications/patents (when applicable)
- Develop level of expertise in specific technical discipline to be recognized as future leading global expert
- Supports 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 (implement) 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 Timeseries 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 plan.
About you
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 experiences of specialization in time series forecasting, in either 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).
Nice to have
- 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.
Your Benefits
We are committed to providing benefits that are competitive and support the needs of our employees.
Application Process
Please be informed that only shortlisted candidates will be notified, and you can find out more about our hiring process here.
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We thank you for your interest in ExxonMobil.
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Equal Opportunity Employer
ExxonMobil is an Equal Opportunity Employer. All qualified applicants will be duly considered for employment.
Voted Top 5 Graduates’ Choice of Employers in Malaysia for Oil and Gas category
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 ExxonMobil, 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, ExxonMobil 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.
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- Location & working pattern
Kuala Lumpur, Federal Territory of Kuala Lumpur, MY, 50088
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