Data Analytics Specialist

Aramco; Saudi Arabia; On-site; SAR 300,000 - 450,000; Full time

Job summary

A leading company in the energy sector is looking for a Data Analytics Specialist to enhance operational efficiency through innovative data solutions. The role involves developing advanced analytics and machine learning models, with a strong emphasis on collaboration with cross-functional teams and continuous improvement of processes. Candidates with a Bachelor’s degree in Data Science or related field and extensive experience in data science and machine learning are encouraged to apply.

Qualifications

• 20 years experience in Data Science or ML required.
• Expertise in MLOps, DevOps, and model deployment frameworks essential.
• Skills in Python, SQL, R, and data visualization tools preferred.

Responsibilities

• Develop advanced analytics use cases to optimize processes and enhance safety.
• Implement MLOps practices to bring ideas from conception to production.
• Collaborate with IT and engineering teams on technical challenges.

Skills

Data Science

Machine Learning

Data Visualization

Data Preprocessing

AI Techniques

Education

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

Master’s or PhD preferred

Tools

Python

R

SQL

Power BI

Azure

Google Cloud

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 at Aramco.

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

As a Data Analytics Engineer, your role will be to lead innovation by utilizing data assets and analytics to create additional value, identifying and solving strategic and tactical business problems to improve operational efficiency.

Responsibilities include:

1. Developing advanced analytics use cases to address technical challenges, optimize processes, and enhance safety and environmental sustainability.
2. Implementing Machine Learning Operations (MLOps) and Development Operations (DevOps) practices to bring ideas from conception to production.
3. Developing and deploying Machine Learning models and pipelines, ensuring their monitoring and scalability.
4. Exploring diverse data sources to improve predictive models and business strategies.
5. Evaluating AI tools and methods for data analysis to improve decision-making.
6. Applying predictive modeling techniques to optimize production and operational efficiencies.
7. Documenting processes according to standards to support development and deployment.
8. Collaborating with cross-functional teams including IT, engineering, and business stakeholders.
9. Participating in technical task forces to investigate incidents using AI/ML techniques.
10. Publishing research and presenting findings at conferences to advance industry knowledge.
11. Fostering a culture of continuous learning and innovation.
12. Providing 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 (Master’s or PhD) 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 model deployment frameworks.
4. Experience in data preprocessing, wrangling, and industry-related problem solving.
5. Proficiency with platforms such as Python, R, SQL, SAS, Scala, and cloud services like Azure and Google Cloud.
6. Skills in visualization tools and UI experience with Power BI or similar.
7. Knowledge of IT architecture, containerization (Docker, Kubernetes), and automation frameworks.
8. Ability to publish research or contribute to industry publications.

Job Posting Duration:

Start Date: 07/10/2025

End Date: 12/31/2025

Working Environment:

Our employees are engaged in world-scale projects, supported by investments in capital and technology. We prioritize talent development through extensive training and workforce development programs, encouraging continuous improvement of sector-specific skills.