(Global Oil Gas) Senior Data Scientist Expert

1 week ago

Anchorage, United States MatchaTalent Full time

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 a Data Scientist Expert, responsible for providing AI- powered solutions to various business functions within Global Manufacturing 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, including engineers and domain experts, to drive data-driven improvements. Gather and preprocess data from various industrial sources, such as sensors, DCS systems, and manufacturing equipment. 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 identify equipment failures and minimize downtime. Explore innovative ideas for applying image, video, and audio analytics to reduce manual efforts, such as visual inspection and 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 comprehensive documentation for data analysis processes, models, and findings. Ensure that data practices adhere to industry regulations and data privacy standards. Continuously monitor and evaluate model performance, making necessary adjustments to maintain accuracy and reliability.

Requirements: This role required candidate to permanently relocate at Dhahran, Saudi Arabia. Hold a Bachelor's or Master's degree in Engineering or Data Science from a premier institute. Have a minimum of 5 years of experience in building data analytics-based products in an industrial context, preferably in petroleum refineries. Possess the ability to identify business problems that can be addressed through data analysis and develop data-driven solutions, including addressing engineering and operational problems and creating computer vision-based products. Demonstrate exceptional analytical and problem-solving skills, with the ability to derive insights and opportunities from data. Understand the Oil & Gas downstream domain to effectively apply data science techniques. Have experience in developing AI/ML-based Digital twins of industrial processes and equipment. Be experienced in applying optimization algorithms in conjunction with AI/ML models. Have expertise in Python for data manipulation, analysis, and modeling, including proficiency in popular libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, etc. Be proficient in deep learning tools such as Keras, TensorFlow, PyTorch, Caffe, etc. Have proficiency in developing, evaluating, and selecting the best ML model based on the problem under consideration, with an engineering sense. Demonstrate the ability to bring ideas from conceptualization to production. Proficiency in visualization tools and packages, as well as the ability to communicate 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.

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