Title:  Data Scientist

Overview

We are seeking a Data Scientist to join our Global Optimizer Department.

The Global Optimizer Department is responsible for driving commercial optimization across Saudi Aramco’s integrated downstream value chain, which includes both domestic and international refining assets. This involves identifying and capturing optimization opportunities that enhance system netback and deliver incremental value to shareholders. The department also collaborates closely with downstream assets, Aramco Trading Company, and key stakeholders to support informed decision-making and agile responses to dynamic market conditions by leveraging advanced analytics, data modeling, and real-time market insights,

Your primary role is to develop and deploy digital solutions that enhance the iGO (intelligent Global Optimizer) platform, enabling data-driven optimization decision support. You will also design and implement advanced analytical models, automate data pipelines, and apply machine learning techniques to improve forecasting, scenario modeling, and optimization sensitivity analysis. By transforming complex data into actionable insights, you will support forward planning, simulation, and continuous learning to refine strategies and maximize the value captured across Saudi Aramco's refining and petrochemical assets.

Key Responsibilities

As the successful candidate you will be required to perform the following:

• Develop and implement advanced data models and machine learning algorithms to support optimization decision-making within the iGO platform.
• Design and automate data pipelines that integrate, cleanse, and enrich large datasets from multiple sources to ensure high-quality inputs for optimization models.
• Build and maintain predictive and prescriptive analytics tools that enhance scenario modeling, forecasting, and back casting capabilities to improve optimization throughput.
• Assess the effectiveness of existing data-driven models and continuously refine them based on feedback loops and performance metrics.
• Perform statistical analysis and sensitivity analysis to identify key optimization levers and prioritize high-impact opportunities across refining and petrochemical assets.
• Collaborate with cross-functional teams to translate complex business requirements into scalable digital solutions that support agile and responsive optimization.
• Ensure that all digital solutions align with enterprise data standards, cybersecurity protocols, and overall IT architecture.
• Document technical specifications and maintain version-controlled repositories to support continuous development and model governance.

Minimum Requirements

• You will hold a Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related field from a recognized and approved program. An advanced degree is preferred.
• You will have at least 10 years’ experience in data analytics, machine learning, or quantitative modeling, including at least 5 years in developing enterprise-level AI and machine learning applications.
• You must have strong programming skills in Python, SQL, and experience with data science libraries and frameworks such as Pandas, Scikit-learn, TensorFlow, or PyTorch.
• You will have the ability to design and manage data pipelines using modern data engineering tools such as Apache Airflow, Spark, or Kafka.
• You will be able to demonstrate a proven track record in deploying analytics solutions in an industrial or energy sector environment.
• You will have strong analytical and problem-solving skills, with the ability to work with cross-functional teams in a dynamic and complex environment.
• You will have excellent communication and interpersonal skills to effectively present findings and technical concepts to both technical and non-technical stakeholders.
• You will also have a solid understanding of cloud platforms such as GCP, Cloudera, Databricks, Palantir Foundry, AWS or Azure, with experience in deploying and managing models in production environments.
• Knowledge of optimization techniques, linear programming, or operations research is preferred.

Work Location and Work Schedule

Work Location: Within Saudi Arabia – To be specified in Job offer

Work Schedule: Full Time - To be specified in Job offer

Job Post Duration

Job posting start date: 1/14/2026

Job posting end date: 12/30/2026