(Global Petroleum Refinery) Senior Data Artificial Intelligence Specialist

This role required candidate to permanently relocate at Dhahran, Saudi Arabia.
About the Company
This company engages in the exploration, production, transportation, and sale of crude oil and natural gas. It operates through the following segments: Upstream, Downstream, and Corporate. The Upstream segment includes crude oil, natural gas and natural gas liquids exploration, field development, and production. The Downstream segment focuses on refining, logistics, power generation, and the marketing of crude oil, petroleum and petrochemical products, and related services to international and domestic customers. The Corporate segment offers supporting services including human resources, finance, and information technology. The company was founded on May 29, 1933 and is headquartered in Dhahran, Saudi Arabia.
Job Summary
We are seeking an Artificial Intelligence Specialist to join our Global Manufacturing Excellence Digitalization and Technology Management (D&TM).
D&TM are responsible for providing AI-powered solutions to various business functions within our Global Manufacturing Excellence admin area. The solutions leverage the latest technological advancements of Artificial Intelligence (AI) and analytics to create business values across the value chain. The Global Manufacturing Excellence organization will be the center of excellence in Global Manufacturing under Downstream business line within This Company for Digital transformation, Artificial Intelligence technologies and data science.
Your primary role will be to work closely with business functions, stakeholders, functional teams to give consultations on AI/ML use case, identify potential value from data, formulate AI and data science ideas and conceptualize them. This role will play a pivotal role in helping our organization to make data-driven decisions and to solve complex problems.
Responsibilities:

• Collaborate with cross-functional teams to drive data-driven improvements.
• Gather and preprocess data from various industrial sources.
• Analyze data to identify opportunities for process optimization, energy efficiency improvements, and cost reduction.
• Implement anomaly detection algorithms to identify abnormal patterns in industrial processes and equipment.
• Develop predictive maintenance models to minimize downtime.
• Apply image, video, and audio analytics to reduce manual efforts like visual inspection/field monitoring of industrial plants.
• Create informative dashboards to communicate insights to operational teams and management.
• Deploy machine learning models into production systems for real-time monitoring and decision-making.
• Maintain documentation for data analysis processes, models, and findings.
• Ensure data practices adhere to industry regulations and data privacy standards.
• Monitor and evaluate model performance, making necessary adjustments to maintain accuracy and reliability.

• This role required candidate to permanently relocate at Dhahran, Saudi Arabia.
• Hold a Bachelor's/Master's degree in Engineering or Data Science from a premier institute.
• Have at least 5 years of experience building data analytics-based products in industrial contexts, preferably in petroleum refineries.
• Ability to identify business problems addressable through data analysis and develop data-driven solutions, including engineering/operational issues and computer vision-based products.
• Possess exceptional analytical and problem-solving skills, with the ability to derive insights and opportunities from data.
• Understanding of the Oil & Gas downstream domain to apply data science effectively.
• Experience in developing AI/ML-based Digital twins of industrial processes/equipment.
• Experience in applying optimization algorithms in line with AI/ML models.
• Expertise in Python for data manipulation, analysis, and modeling, including popular libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, etc.
• Proficiency in deep learning tools such as Keras, TensorFlow, PyTorch, Caffe, etc.
• Proficiency in developing, evaluating, and selecting the best ML model based on the problem under consideration with an engineering sense.
• Ability to bring ideas from conceptualization to productionizing.
• Proficiency in visualization tools and packages, and in communicating data science topics to non-technical audiences.
• Basic project management skills to plan, execute, and deliver data science projects on time and within scope are preferred.