Gas Business Modeler

Apply now » Title: Gas Business Modeler Job Req ID: 17028 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. Job Overview: We are seeking a Gas Business Modeler to join our Gas Operations Technical Support Division (GOTSD) under Gas Operations Technical Support & Planning Department (GOTS&PD) GOTSD is responsible for the strategic growth and optimization of the gas business, integrating technical expertise, and digital and technologies innovation. ITMG also oversees the Master Gas Network planning, while optimizing the gas supply portfolio through advanced modeling and cost-benefit frameworks. It focuses on deploying cutting-edge technologies—such as AI, IoT, and digital twins to deliver high-impact solutions to shape the future of gas operations. Your primary role is to provide technical and analytical skills to support decision decision-making, design, optimization, and operational efficiency involved in gas process simulation, pipeline or network modeling, equipment performance modeling, or economic forecasting. Key Responsibilities: As the successful candidate you will be required to perform the following: Maintain and apply mathematical, computational, or simulation models to support engineering design, operational analysis, project planning, and performance optimization in gas sector in order to simulate real-world conditions, test scenarios, and predict outcomes to guide engineering and business decisions. Develop and maintain steady-state or dynamic simulation models using industry-standard software (e.g., HYSYS, PROSPER, GAP, PipePhase, etc.). Create simulation models for process units, pipeline networks, production systems, or processing facilities. Apply thermodynamic, hydraulic, or economic principles to ensure model accuracy. Collect and validate data from field measurements, historical performance, or engineering studies. Ensure data consistency and reliability for accurate modeling and forecasting. Run simulations under various operating conditions or scenarios (e.g., equipment failure, capacity changes, production decline, new well connections). Analyze results to identify performance bottlenecks, capacity limits, or optimization opportunities. Recommend design or operational changes based on model findings. Provide modeling support for FEED (front-end engineering Design ) studies, project design, and operational troubleshooting. Support capital project evaluations and feasibility studies with technical insights from models. Test and validate models against real-time or historical data to ensure accuracy. Calibrate models to match field behavior and improve predictive capability. Minimum requirements: As the successful candidate you will hold a Bachelor degree in Engineering (preferably Chemical, or Mechanical Engineering) You will have minimum of 10 years of experience in gas process modeling and simulation, preferably in gas sector. Professional certifications (e.g., in simulation software or project economics) are preferred. Experience in model-based decision support or digital transformation initiatives (e.g., digital twins, predictive analytics) is a plus. You will have proficiency in Process simulation such as: HYSYS, PRO/II, Aspen Plus. You will also have skills in production systems modeling such as: PROSPER, GAP, PIPESIM, Preferably with Pipeline network modeling such as: PLEXSYS, OLGA (for dynamic models). You will have a strong understanding of Thermodynamics, fluid mechanics, mass and energy balances. You will have experience in Data analysis and visualization tools (e.g., Excel, Python, MATLAB, Power BI). You will have experience in Economic modeling (e.g., NPV, IRR, cash flow projections), Preferably familiarity with Saudi Aramco standards and procedures. You will also have analytical thinking and problem-solving skills as well as attention to details and accuracy in modeling. Work Location and Work Schedule: Work location: Within Saudi Arabia –

Bachelor degree in Engineering (Chemical or Mechanical preferred). Minimum of 10 years of experience in gas process modeling and simulation. Professional certifications in simulation software or project economics are preferred.

Maintain and apply mathematical, computational, or simulation models to support engineering design, operational analysis, project planning, and performance optimization in gas sector. Develop and maintain steady-state or dynamic simulation models using industry-standard software (e.g., HYSYS, PROSPER, GAP, PipePhase). Create simulation models for process units, pipeline networks, production systems, or processing facilities. Collect and validate data from field measurements, historical performance, or engineering studies. Run simulations under various operating conditions or scenarios. Analyze results to identify bottlenecks or optimization opportunities. Recommend design or operational changes based on model findings. Provide modeling support for FEED studies, project design, and operational troubleshooting. Support capital project evaluations and feasibility studies with technical insights from models. Calibrate models to match field behavior and improve predictive capability.