Downstream Data Scientist

Apply now » Title: Downstream Data Scientist Job Req ID: 17886 Description: Aramco energizes the world economy. 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 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 We are seeking a Data Scientist Specialist to our Downstream Transformation & Business Excellence Department (DST&BED). DST&BED empowers the Downstream Admin Areas with advanced analytics, digital tools, and data-driven insights to improve reliability, optimize operations, accelerate decision-making, and enable strategic digital transformation. The organization is responsible for designing advanced analytical models, developing scalable digital solutions, and supporting enterprise-level digital programs. Your primary role is to design, develop, and operationalize advanced machine learning models that support downstream optimization, predictive maintenance, and performance enhancement. You will work with complex datasets, apply advanced statistical and AI techniques, and ensure models deliver measurable value across operational areas. Key Responsibilities As the successful candidate you will be required to perform the following: Develop machine learning, statistical, and predictive models for downstream operational use cases. Assess data quality, perform data cleansing, and prepare datasets for model development. Explore advanced analytical techniques such as deep learning, time-series modelling, anomaly detection, and optimization algorithms. Validate, test, and refine models to ensure accuracy, reliability, and stability. Prepare technical documentation and present analytical results to stakeholders. Support integration of models into digital platforms and operational systems. Evaluate emerging data science methods and recommend approaches that improve model performance. Collaborate with engineers, analysts, and solution architects to translate operational challenges into data-driven solutions. Minimum Requirements You will hold a Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, or a related field from a recognized and approved program. You will have 15 years of experience in data science or advanced analytics, including at least 10 years working on industrial analytics or digital solutions. You will have strong knowledge of machine learning, statistical modelling, and data engineering techniques. You must have proven experience developing and deploying models into production environments. You will be able to demonstrate proficiency in Python or similar programming languages. Experience with cloud platforms, databases, and visualization tools is preferred. You will have the ability to translate complex data concepts into business insights. 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 Posting Duration Job posting start date: 09/15/2026 Job posting end date: 09/14/2027 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 Apply now » Find similar jobs: For US Applicants, For European Applicants Careers Home Privacy Statement Email Fraud Opens in a new tab. Opens in a new tab. Opens in a new tab. © Saudi Arabian Oil Company, 2021

Bachelor’s Degree in Computer Science, Data Science, Engineering, Mathematics, or a related field from a recognized and approved program. 15 years of experience in data science or advanced analytics, including at least 10 years working on industrial analytics or digital solutions. Strong knowledge of machine learning, statistical modelling, and data engineering techniques. Proven experience developing and deploying models into production environments. Proficiency in Python or similar programming languages. Experience with cloud platforms, databases, and visualization tools is preferred. Ability to translate complex data concepts into business insights.

Develop machine learning, statistical, and predictive models for downstream operational use cases. Assess data quality, perform data cleansing, and prepare datasets for model development. Explore advanced analytical techniques such as deep learning, time-series modelling, anomaly detection, and optimization algorithms. Validate, test, and refine models to ensure accuracy, reliability, and stability. Prepare technical documentation and present analytical results to stakeholders. Support integration of models into digital platforms and operational systems. Evaluate emerging data science methods and recommend approaches that improve model performance. Collaborate with engineers, analysts, and solution architects to translate operational challenges into data-driven solutions.