Saudi Aramco
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Petroleum Engineering / Data Management

Job Description and Requirements

As a successful candidate, you should hold a bachelor’s degree Computer science BS degree with a master/specialization in artificial intelligence, data science or data analytics. MSc or PhD is desirable. 

You must have a minimum of 10 years of intensive experience in the area of data management. Technical publications are valued but in-depth practical experience is paramount. 

You must have a minimum of 5 years of experience in the field of data science, advanced data analytics or artificial intelligence domains. Mastery of machine learning algorithms, which include: Deep Learning algorithms (Feed forward neural networks, convolutional neural networks, recursive neural networks), classification algorithms (Random forest, C45, SVM, Bayesian, KNN), clustering algorithms (K-means, hierarchical, DBSCAN), reinforcement Learning and recommendation systems. 

You should have the ability to work effectively in multi-disciplinary teams and to communicate ideas clearly with specialists in petroleum engineering data management, reservoir characterization and geologic modeling, petro-physical evaluation, core analysis, reservoir management, and production engineering. 

You should have proficiency in SQL to access, communicate and work with data. 

You should have good knowledge in data visualization to translate results into figure and graphs.

Duties & Responsibilities:
You are expected to be able to perform the following: 

Lead and participate in advanced data analytics studies and IR 4.0 projects, which include EDA, data pre-processing, model construction, model evaluation and calibration. 

Apply latest IR 4.0 and advanced data analytics methods, and keep up-to-date with the latest technologies. 

Conduct comprehensive petrophysical studies and analyses by integrating logging tool responses, rock, fluid and production data for formation evaluation and reservoir surveillance. 

Design and oversee core and fluid studies to enhance petrophysical models. 

Perform and oversee accurate Plant and Well Allocation processes. 

Enhance data quality in the well database by enhancing data flow processes. 

Propose data model design/business rules enhancements for data quality improvements. 

Develop and enforce data access control measures to maintain Petroleum Engineering data confidentiality. 

Conduct training for professionals with proper training materials. 

Act as technical advisor to management regarding best practices for advanced data analytics and data science topics.