Data Scientist (For Relocation to Dhahran, Saudi Arabia)

Aramco energizes the world economy.

Aramco occupies a unique position in the global energy industry. We are the world's largest producer of hydrocarbons (oil and gas), with the lowest upstream carbon intensity 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 along with a commitment to enhance Aramco’s value to society.

Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generations’ spanning view of the future, born of our nine decades 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 that we supply.

We are one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.

Overview

Saudi Aramco is seeking an Engineer for the development and implementation of data analytics solutions to join the Process & Control Systems Department, Digital Engineering Solutions Division, based in Dhahran, Saudi Arabia.

The successful candidate will lead innovation within the business and defines how the business creates additional value through the utilization of its data assets and analytics. Engages with SMEs to identify & solve strategic & tactical analytic business problems to enhance operational efficiency.

Key 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 MLOps and DevOps practices.
• Develop and optimize ML models and pipelines, ensuring their efficient deployment, monitoring, and scaling.
• Explore diverse data sources to improve predictive modeling and optimize business strategies.
• Assess 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.
• Provide leadership and mentorship to junior team members and specialists.
• Contribute to technical task forces investigating incidents and solving domain-specific problems using AI/ML techniques.
• Publish research papers for peer-reviewed journals and presents findings to other organizations and conferences to advance industry knowledge.
• Promotes a learning environment through knowledge-sharing, and fosters a culture of continuous learning and innovation.

Minimum Requirements:

• A Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field from a recognized institution.
• An advanced degree (Master’s or PhD) focused on Data Science, AI, or ML Engineering with a background in Engineering is highly preferred.
• 10-15 years of overall experience, with at least 5 years of hands-on experience in Data Science, NLP, Computer Vision, and/or ML projects in the industry.
• Strong hands-on 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 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 commercial cloud architecture and deploying models in cloud environments (e.g., Google Cloud, Azure).
• 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.

Working environment

Our high-performing employees are drawn by the challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly.

At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none. And because, as a global energy company, we are faced with addressing some of the world’s biggest technical, logistical and environmental challenges, we invest heavily in talent development.

We have a proud history of educating and training our workforce over many decades. Employees at all levels are encouraged to improve their sector-specific knowledge and competencies through our workforce development programs – one of the largest in the world.

Country/Region: SA