aramco
About Aramco
Aramco occupies a special position in the global energy industry. We are one of the world’s largest producers of hydrocarbon energy and chemicals, with among the lowest Upstream carbon intensities of any major producer.
With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world while enhancing Aramco’s value to society.
Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generational spanning view of the future, born of our nine decades of experience as responsible stewards of the Kingdom’s vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy we supply.
We are one of the most profitable companies in the world and among the top five global companies by market capitalization.
Position Overview We are seeking a Data Analytics Specialist to join our Digital Engineering Solutions Division under the Process & Control Systems Department.
As a Data Analytics Engineer your role will be to lead innovation within the business and define how the business creates additional value through the utilization of its data assets and analytics. You will identify and solve strategic and tactical analytic business problems to enhance operational efficiency.
Duties and Responsibilities
Identify and develop advanced analytics use cases to resolve complex technical challenges, optimize processes, enhance revenue, ensure environmental sustainability, and improve safety.
Drive ideas from conception to production using best‑in‑class Machine Learning Operations (MLOps) and Development Operations (DevOps) practices.
Develop and optimize Machine Learning (ML) models and pipelines, ensuring efficient deployment, monitoring, and scaling.
Explore diverse data sources to improve predictive modeling and optimize business strategies.
Assess Artificial Intelligence (AI) tools and methods for data analysis, enhancing business impact and decision‑making.
Implement predictive modeling techniques to optimize production facilities, revenue streams, and operational efficiencies.
Generate documentation in line with established standards to support the development and deployment process.
Collaborate with cross‑functional teams, including IT, engineering, and business stakeholders, to drive data‑driven solutions.
Contribute to technical task forces investigating incidents and solving domain‑specific problems using AI/ML techniques.
Publish research papers for peer‑reviewed journals and present findings at conferences to advance industry knowledge.
Promote a learning environment through knowledge sharing and foster a culture of continuous learning and innovation.
Provide leadership and mentorship to junior team members and specialists.
Minimum Requirements
Bachelor’s degree in Data Science, Computer Science, Engineering or related field. An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering is highly preferred.
20 years of overall experience, with hands‑on experience in Data Science, NLP, Computer Vision, and/or ML projects in industry.
Expertise in MLOps, DevOps, AIOps, DataOps and related operational frameworks for model deployment, monitoring, and automation.
Experience in data collection, cleaning, preprocessing, and wrangling for industry‑related problems based on domain knowledge.
Proficiency in platforms such as Python, R, SQL, SAS, Scala, and cloud platforms such as Azure and Google Cloud (Vertex AI).
Expertise in visualization tools and packages; UI experience with Power BI or similar tools.
Experience with IT architecture and deploying models in on‑prem environments.
Strong understanding of CI/CD pipelines, containerization (Docker, Kubernetes), and automation frameworks.
Demonstrated ability to publish research or contribute to industry knowledge through journal papers, conference proceedings, or whitepapers.
Job Posting Dates Start date: 07/10/2025. End date: 12/31/2025.
Working Environment Our high‑performing employees are drawn by challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly. We invest heavily in talent development and support world‑scale projects, backed by second‑to‑none capital and technology investments. Our workforce development programs are among the largest in the world, encouraging continuous improvement of sector‑specific knowledge and competencies.
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With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world while enhancing Aramco’s value to society.
Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generational spanning view of the future, born of our nine decades of experience as responsible stewards of the Kingdom’s vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy we supply.
We are one of the most profitable companies in the world and among the top five global companies by market capitalization.
Position Overview We are seeking a Data Analytics Specialist to join our Digital Engineering Solutions Division under the Process & Control Systems Department.
As a Data Analytics Engineer your role will be to lead innovation within the business and define how the business creates additional value through the utilization of its data assets and analytics. You will identify and solve strategic and tactical analytic business problems to enhance operational efficiency.
Duties and Responsibilities
Identify and develop advanced analytics use cases to resolve complex technical challenges, optimize processes, enhance revenue, ensure environmental sustainability, and improve safety.
Drive ideas from conception to production using best‑in‑class Machine Learning Operations (MLOps) and Development Operations (DevOps) practices.
Develop and optimize Machine Learning (ML) models and pipelines, ensuring efficient deployment, monitoring, and scaling.
Explore diverse data sources to improve predictive modeling and optimize business strategies.
Assess Artificial Intelligence (AI) tools and methods for data analysis, enhancing business impact and decision‑making.
Implement predictive modeling techniques to optimize production facilities, revenue streams, and operational efficiencies.
Generate documentation in line with established standards to support the development and deployment process.
Collaborate with cross‑functional teams, including IT, engineering, and business stakeholders, to drive data‑driven solutions.
Contribute to technical task forces investigating incidents and solving domain‑specific problems using AI/ML techniques.
Publish research papers for peer‑reviewed journals and present findings at conferences to advance industry knowledge.
Promote a learning environment through knowledge sharing and foster a culture of continuous learning and innovation.
Provide leadership and mentorship to junior team members and specialists.
Minimum Requirements
Bachelor’s degree in Data Science, Computer Science, Engineering or related field. An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering is highly preferred.
20 years of overall experience, with hands‑on experience in Data Science, NLP, Computer Vision, and/or ML projects in industry.
Expertise in MLOps, DevOps, AIOps, DataOps and related operational frameworks for model deployment, monitoring, and automation.
Experience in data collection, cleaning, preprocessing, and wrangling for industry‑related problems based on domain knowledge.
Proficiency in platforms such as Python, R, SQL, SAS, Scala, and cloud platforms such as Azure and Google Cloud (Vertex AI).
Expertise in visualization tools and packages; UI experience with Power BI or similar tools.
Experience with IT architecture and deploying models in on‑prem environments.
Strong understanding of CI/CD pipelines, containerization (Docker, Kubernetes), and automation frameworks.
Demonstrated ability to publish research or contribute to industry knowledge through journal papers, conference proceedings, or whitepapers.
Job Posting Dates Start date: 07/10/2025. End date: 12/31/2025.
Working Environment Our high‑performing employees are drawn by challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly. We invest heavily in talent development and support world‑scale projects, backed by second‑to‑none capital and technology investments. Our workforce development programs are among the largest in the world, encouraging continuous improvement of sector‑specific knowledge and competencies.
#J-18808-Ljbffr