Data Analytics Specialist

Saudi Aramco; Saudi Arabia; On-site; SAR 200,000 - 300,000; Full time

Job summary

A leading company in Saudi Arabia is seeking a Data Analytics Specialist to enhance value through data and analytics within the Digital Engineering Solutions Division. This role involves developing analytics use cases, utilizing machine learning practices, and collaborating across teams to drive innovation. Candidates should have a strong background in data science, extensive experience in machine learning, and proven expertise in various data analysis tools.

Qualifications

• 20 years of experience in Data Science, NLP, Computer Vision, or ML projects.
• Expertise in MLOps, DevOps, AIOps, DataOps frameworks.
• Knowledge of CI/CD pipelines and automation frameworks.

Responsibilities

• Identify and develop advanced analytics use cases to resolve complex challenges.
• Collaborate with teams to drive data-driven solutions.
• Document processes and ensure deployment according to standards.

Skills

Data Science

Machine Learning

Artificial Intelligence

Python

Data Analytics

Problem Solving

Education

Bachelor’s degree in Data Science, Computer Science, Engineering, or related field

Advanced degree preferred

Tools

Python

R

SQL

SAS

Scala

Azure

Google Cloud

Power BI

Job description

Position: Data Analytics Specialist

We are seeking a Data Analytics Specialist to join our Digital Engineering Solutions Division under the Process & Control Systems Department.

The Process and Control Systems Department provides services in process engineering, automation, new energy, and digitalization within Aramco.

As a Data Analytics Engineer, your role will be to lead innovation and define how the business creates value through data assets and analytics. You will identify and solve strategic and tactical business problems to improve operational efficiency.

Responsibilities:

1. Identify and develop advanced analytics use cases to resolve complex challenges, optimize processes, enhance revenue, and improve safety and environmental sustainability.
2. Drive ideas from conception to production using best practices in Machine Learning Operations (MLOps) and Development Operations (DevOps).
3. Develop and optimize ML models and pipelines, ensuring their deployment, monitoring, and scaling.
4. Explore diverse data sources to improve predictive modeling and business strategies.
5. Assess AI tools and methods for data analysis to enhance decision-making.
6. Implement predictive modeling techniques to optimize production and operational efficiencies.
7. Document processes according to standards to support development and deployment.
8. Collaborate with IT, engineering, and business teams to drive data-driven solutions.
9. Contribute to technical task forces on incidents and domain-specific problems using AI/ML techniques.
10. Publish research papers and present findings at conferences to advance industry knowledge.
11. Promote a culture of continuous learning and innovation.
12. Provide leadership and mentorship to junior team members.

Minimum Requirements:

1. Bachelor’s degree in Data Science, Computer Science, Engineering, or related field; an advanced degree is highly preferred.
2. 20 years of experience in Data Science, NLP, Computer Vision, or ML projects.
3. Expertise in MLOps, DevOps, AIOps, DataOps, and related frameworks.
4. Experience in data preprocessing, wrangling, and collection.
5. Proficiency in Python, R, SQL, SAS, Scala, and cloud platforms like Azure and Google Cloud.
6. Experience with visualization tools and UI tools like Power BI.
7. Knowledge of IT architecture and model deployment in on-prem environments.
8. Understanding of CI/CD pipelines, containerization, and automation frameworks.
9. Research publication experience or contributions to industry knowledge.

Job Posting Duration:

Start Date: 07/10/2025

End Date: 12/31/2025

Working Environment:

Our employees are supported by investment in capital and technology, working on world-scale projects. We emphasize talent development through extensive training and workforce development programs.