Data Scientist - RELOCATE TO SAUDI ARABIA REQUIRED

Title: Data Scientist

Location: Dhahran, Saudi Arabia (full time expat)

Description:

Aramco occupies a unique position in the global energy industry. We are the world's largest oil and gas company, and one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.

This position is located at our corporate headquarters in the Kingdom of Saudi Arabia.

Overview

We are seeking a Data Scientist to join our Artificial Intelligence and Analytics Organization (AI&A).

AI&A, within our Digital transformation office, is dedicated to realize business added value from leveraging the latest technological advancements of Artificial Intelligence (AI) and analytics. We are a center of excellence in Saudi Aramco for Artificial Intelligence technologies and data science.

Your primary role is to identify potential value from data, formulate AI and data science ideas and conceptualize them.

Key Responsibilities

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

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company data sources to drive optimization and improvement of product development, and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to datasets.
• Support ideation endeavors in packaging new ideas/products and preparing them for minimal viable product development.
• Assess AI applicability in enhancing current business processes.

Minimum Requirements

• As the successful candidate you must hold a Master of Science or PhD degree in data science, computer science, computer vision, applied mathematics or a related field.
• You must have a minimum of 8 years of hands-on experience in Data Science & AI projects (Generative AI, Computer Vision, Natural Language Processing (NLP), Time Series). Experience in the energy sector is a plus.
• You must be able to demonstrate experience of bringing ideas from conceptualization to productionalization using the right tools (e.g. mlflow, kubeflow, tensorlight, etc).
• You must also be able to showcase a very strong expertise in data collection, cleaning, and preprocessing, and wrangling.
• You should be fluent in either R, or Python; both is preferred, and familiarity with golang is a plus.
• You should have at least 5 years of experience in building computer vision-based product.
• You should be able to apply transfer learning on models like, VGG16, LeNet, ResNet, AlexNet, etc
• You must be proficient in deep learning tools keras, tensorflow, pytorch, cafee, opencv and/or dlib, and scikit-image.
• You must be able to build object detection models, face/gesture recognition, and identification engines.
• You should be experienced in Information Retrieval (Content Recommendation, Search Metrics, Search Query, document classification, entity recognition, topic modelling, etc).
• You should be proficient in transfer learning and in fine tuning open-sourced models like BERT.
• You should have least 5 years of experience in building time series forecasting models.
• You should be expert in time series forecasting models and in using technologies like LSTMs, Prophet, and time series analysis.
• You should be proficient in using sklearn pandas, numpy, plotly, seaborn, and relevant R libraries if R is their preferred language.
• Willingness and ability to relocate to Saudi Arabia on a full-time, permanent basis.

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.