Digital Oilfields Specialist - AI Analytics
Posted date [2026-06-28]
(ID: 47173)
 |
Founded in 1971, ADNOC is a leading diversified energy group, wholly owned by the Abu Dhabi Government. Our network of fully integrated businesses operates across the energy value chain, helping us to responsibly meet the demands of an ever-changing energy market.
Already in the top tier of the lowest carbon intensity oil and gas producers in the world, we are taking significant steps to make today’s energy cleaner while investing in the clean energies of tomorrow, strengthening our position as a reliable and responsible global energy provider. We are allocating an initial $23 billion to advance and accelerate lower-carbon solutions, investing in new energies and decarbonization technologies to enable our net zero by 2045 ambition and our commitment to zero methane emissions by 2030. ... |
Job Description and Requirements
Digital Oilfields Specialist - AI AnalyticsJob Snapshot
Role: Digital Oilfields Specialist - AI Analytics
Location: Abu Dhabi Emirate, United Arab Emirates
Industry: Oil and Energy
Function: Information Technology
Experience: Minimum 10 years in large-scale data science, data analytics, AI, and software development within oil and gas
Job Type: Full-time
Position Overview
Digital Oilfields Specialist - AI Analytics in Abu Dhabi Emirate, United Arab Emirates is an Oil and Energy hiring opportunity focused on artificial intelligence strategy, digital oilfield transformation, data science, big data analytics, predictive modeling, machine learning, and operational excellence. This role supports ADNOC Offshore by developing AI-driven solutions, data analytics frameworks, digital oilfield strategies, and scalable models that improve production performance, enhance oil recovery, support safer operations, and solve complex exploration, development, drilling, and production challenges.
Job Details
Country: United Arab Emirates
City: Abu Dhabi Emirate
Industry: Oil and Energy
Function:
Information Technology
Salary: 45000-65000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Full-time
Role Context
The Digital Oilfields Specialist - AI Analytics will help advance digital oilfield capability by combining petroleum domain knowledge, artificial intelligence, machine learning, data science, big data platforms, and advanced visualization. The position works with real-time operational data, sensor data, maintenance logs, images, text, metering information, and complex technical datasets to identify insights and convert them into practical business and technical improvements. By engaging discipline engineers, subject matter experts, IT teams, operations excellence groups, vendors, consultants, and ADNOC Group counterparts, the role supports smarter decisions, improved asset performance, and stronger digital transformation across offshore operations.
Key Responsibilities
* Develop and support implementation of digital oilfield strategies and plans in line with company objectives, operational priorities, and recovery improvement goals.
* Maintain the Digital Oilfields strategy and benchmark digital oilfield practices against ADNOC Group Companies.
* Design, implement, and maintain ADNOC Offshore artificial intelligence strategy for core business and technical domains related to exploration, development, drilling, and production.
* Develop AI strategy documents, technical guidelines, and minimum requirements for departments, programs, and digital oilfield projects.
* Work closely with discipline engineers, subject matter experts, operations teams, and IT stakeholders to develop AI systems that learn from data and adapt to operational conditions.
* Conduct brainstorming sessions and technical workshops to identify business and technical problems suitable for AI, machine learning, analytics, and automation.
* Prioritize AI opportunities based on value, feasibility, operational impact, data availability, and alignment with offshore business objectives.
* Conduct market research and technology scans covering artificial intelligence, machine learning, data science, analytics platforms, and emerging digital oilfield technologies.
* Compare and evaluate leading technologies, including industry-ranked tools and solutions, for relevance to oil and gas operations.
* Develop scalable AI tools using deep learning models for use cases such as voice recognition, natural language processing, time series prediction, and operational decision support.
* Collect and define technical and business requirements for production-level AI applications and prepare deployment roadmaps.
* Model complex offshore operational problems using algorithms, statistical models, data mining methods, and visualization techniques.
* Recommend continuous improvements to methods, algorithms, model structures, and analytical processes based on findings and new information.
* Define business metrics for AI and analytics projects and monitor improvements across multiple iterations.
* Conduct workshops to help technical departments understand data science principles, mathematical models, statistical validation, and AI-driven problem solving.
* Build multidisciplinary teams capable of defining, modeling, and solving domain-specific operational and technical challenges.
* Design and launch complex analytical models and lead the development of big data capabilities across cross-functional initiatives.
* Work with structured and unstructured data, including sensor data, maintenance logs, datasheets, images, voice, text, and metering data.
* Build, validate, maintain, and monitor predictive models that support oil and gas business decisions.
* Educate IT and business stakeholders on hypothesis testing, statistical validation, model performance, data-driven experimentation, and analytics adoption.
* Conduct scoping sessions and workshops with technical departments to select the right data, tools, methods, and analytics approaches.
* Track and monitor performance of decision support systems using algorithmic and statistical models.
* Conduct proof of concept initiatives, share findings internally, and identify opportunities for pilot project deployment.
* Design and develop scalable data analytics platforms and solutions for advanced offshore analytics use cases.
* Assess, benchmark, and select data analytics technologies for integration into big data platforms.
* Provide guidance and mentoring to developers and technical teams on data analytics design, model development, and implementation practices.
* Liaise with ADNOC teams to help build and mentor a new team of data scientists.
* Identify available and relevant data sources, including internal and external data, and automate data collection where practical.
* Support analysis of data volume, speed, variety, patterns, and other characteristics required for analytics initiatives.
* Capture, prepare, and process structured and unstructured data required to build models for oil and gas business challenges.
* Provide input for team and department budgets and support implementation of approved work plans.
* Investigate significant budget variances and highlight findings to support effective performance and cost control.
* Contribute to approved performance objectives for the team and department.
* Design and implement new tools and techniques to improve operational process quality, data-driven efficiency, and analytical decision-making.
* Identify process improvements against best practices and ISO standards to develop intelligent solutions for functional challenges.
* Plan, supervise, and coordinate assigned activities to meet functional objectives.
* Train and develop assigned staff to improve technical proficiency, analytics capability, and section performance.
* Implement approved policies, processes, systems, standards, and procedures in line with company and international standards.
* Comply with HSE policies, controls, sustainability guidelines, applicable legislation, and ADNOC Code of Practices.
* Provide inputs for section MIS reports, progress reports, management updates, and performance summaries.
Ideal Profile
* Bachelor’s Degree in Engineering, Artificial Intelligence, Robotics, Petroleum, Computer Science, Data Science, or an equivalent discipline.
* Minimum 10 years of experience in large-scale data science, data analytics, artificial intelligence, and software development within the Oil and Energy sector.
* Strong understanding of natural language processing, machine learning, artificial neural networks, deep learning, statistical modeling, and predictive analytics.
* Strong hands-on experience with machine learning APIs and computational packages such as TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, and statsmodels.
* Strong knowledge of Python, SQL, and R.
* Familiarity with Scala, Java, C, C++, version control, and Matlab is an advantage.
* Experience using business intelligence and visualization tools such as Spotfire, Tableau, or similar platforms.
* Experience with data mining, visualization, data preparation, preprocessing, feature engineering, feature selection, model training, classification, and regression.
* Experience with supervised and unsupervised machine learning algorithms.
* Strong background in data capture, aggregation, collation, manipulation, and analysis of large datasets.
* Experience with big data frameworks such as Hadoop and Spark.
* Practical ability to work with real-time data, sensor data, maintenance logs, datasheets, images, voice, text, metering data, and other oil and gas data sources.
* Strong analytical mindset with solid mathematics, statistics, business insight, and problem-solving capability.
* Experience building AI roadmaps, proof of concepts, pilot projects, decision support systems, and scalable production-level analytics applications.
* Ability to work with discipline engineers, petroleum engineers, drilling teams, production teams, operations excellence groups, IT representatives, procurement teams, vendors, and consultants.
* Excellent communication, presentation, facilitation, and stakeholder engagement skills.
* Proficient in English with the ability to explain technical AI and analytics concepts to business and engineering audiences.
* International certifications in project management, process improvement, standardization, or technology implementation are advantageous.
Skills Set
* Digital oilfields
* Artificial intelligence
* Data science
* Data analytics
* Machine learning
* Deep learning
* Big data analytics
* Predictive modeling
* Statistical modeling
* Natural language processing
* Artificial neural networks
* Time series prediction
* Data mining
* Data visualization
* Decision support systems
* AI strategy
* AI guidelines
* Digital oilfield strategy
* Offshore analytics
* Production optimization analytics
* Exploration analytics
* Development analytics
* Drilling analytics
* Sensor data analytics
* Real-time data processing
* Structured data
* Unstructured data
* Feature engineering
* Feature selection
* Model training
* Classification
* Regression
* Supervised learning
* Unsupervised learning
* TensorFlow
* Theano
* PyTorch
* Keras
* Scikit-Learn
* NumPy
* SciPy
* Pandas
* statsmodels
* Python
* SQL
* R
* Scala
* Java
* C
* C++
* Matlab
* Hadoop
* Spark
* Spotfire
* Tableau
* Proof of concept development
* Pilot project deployment
* Data platform design
* Technology benchmarking
* Vendor evaluation
* Technical workshops
* Stakeholder engagement
* MIS reporting
* HSE compliance
* ADNOC Code of Practices
Why Join Us
This opportunity is ideal for an experienced AI and data science professional who wants to drive digital oilfield transformation in Abu Dhabi Emirate, United Arab Emirates. The role offers exposure to advanced analytics, offshore production intelligence, AI strategy, big data platforms, predictive models, operational excellence, and cross-functional digital transformation within the Oil and Energy sector. It is a strong career step for someone who can combine technical AI depth, oil and gas domain knowledge, real-time data insight, and scalable solution delivery to improve safety, recovery, efficiency, and business performance.
About the Company
ADNOC Group is a leading energy company headquartered in Abu Dhabi, United Arab Emirates, with operations across the full oil and gas value chain. The group plays a major role in energy production, digital transformation, industrial development, and long-term economic growth for the UAE. Through its offshore, operations excellence, research, digital, and technology functions, ADNOC Group offers professionals the opportunity to contribute to advanced Oil and Energy programs where artificial intelligence, data analytics, digital oilfields, operational safety, and production optimization are essential to future-ready performance.
Salary: 45000-65000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Full-time
Role Context
The Digital Oilfields Specialist - AI Analytics will help advance digital oilfield capability by combining petroleum domain knowledge, artificial intelligence, machine learning, data science, big data platforms, and advanced visualization. The position works with real-time operational data, sensor data, maintenance logs, images, text, metering information, and complex technical datasets to identify insights and convert them into practical business and technical improvements. By engaging discipline engineers, subject matter experts, IT teams, operations excellence groups, vendors, consultants, and ADNOC Group counterparts, the role supports smarter decisions, improved asset performance, and stronger digital transformation across offshore operations.
Key Responsibilities
* Develop and support implementation of digital oilfield strategies and plans in line with company objectives, operational priorities, and recovery improvement goals.
* Maintain the Digital Oilfields strategy and benchmark digital oilfield practices against ADNOC Group Companies.
* Design, implement, and maintain ADNOC Offshore artificial intelligence strategy for core business and technical domains related to exploration, development, drilling, and production.
* Develop AI strategy documents, technical guidelines, and minimum requirements for departments, programs, and digital oilfield projects.
* Work closely with discipline engineers, subject matter experts, operations teams, and IT stakeholders to develop AI systems that learn from data and adapt to operational conditions.
* Conduct brainstorming sessions and technical workshops to identify business and technical problems suitable for AI, machine learning, analytics, and automation.
* Prioritize AI opportunities based on value, feasibility, operational impact, data availability, and alignment with offshore business objectives.
* Conduct market research and technology scans covering artificial intelligence, machine learning, data science, analytics platforms, and emerging digital oilfield technologies.
* Compare and evaluate leading technologies, including industry-ranked tools and solutions, for relevance to oil and gas operations.
* Develop scalable AI tools using deep learning models for use cases such as voice recognition, natural language processing, time series prediction, and operational decision support.
* Collect and define technical and business requirements for production-level AI applications and prepare deployment roadmaps.
* Model complex offshore operational problems using algorithms, statistical models, data mining methods, and visualization techniques.
* Recommend continuous improvements to methods, algorithms, model structures, and analytical processes based on findings and new information.
* Define business metrics for AI and analytics projects and monitor improvements across multiple iterations.
* Conduct workshops to help technical departments understand data science principles, mathematical models, statistical validation, and AI-driven problem solving.
* Build multidisciplinary teams capable of defining, modeling, and solving domain-specific operational and technical challenges.
* Design and launch complex analytical models and lead the development of big data capabilities across cross-functional initiatives.
* Work with structured and unstructured data, including sensor data, maintenance logs, datasheets, images, voice, text, and metering data.
* Build, validate, maintain, and monitor predictive models that support oil and gas business decisions.
* Educate IT and business stakeholders on hypothesis testing, statistical validation, model performance, data-driven experimentation, and analytics adoption.
* Conduct scoping sessions and workshops with technical departments to select the right data, tools, methods, and analytics approaches.
* Track and monitor performance of decision support systems using algorithmic and statistical models.
* Conduct proof of concept initiatives, share findings internally, and identify opportunities for pilot project deployment.
* Design and develop scalable data analytics platforms and solutions for advanced offshore analytics use cases.
* Assess, benchmark, and select data analytics technologies for integration into big data platforms.
* Provide guidance and mentoring to developers and technical teams on data analytics design, model development, and implementation practices.
* Liaise with ADNOC teams to help build and mentor a new team of data scientists.
* Identify available and relevant data sources, including internal and external data, and automate data collection where practical.
* Support analysis of data volume, speed, variety, patterns, and other characteristics required for analytics initiatives.
* Capture, prepare, and process structured and unstructured data required to build models for oil and gas business challenges.
* Provide input for team and department budgets and support implementation of approved work plans.
* Investigate significant budget variances and highlight findings to support effective performance and cost control.
* Contribute to approved performance objectives for the team and department.
* Design and implement new tools and techniques to improve operational process quality, data-driven efficiency, and analytical decision-making.
* Identify process improvements against best practices and ISO standards to develop intelligent solutions for functional challenges.
* Plan, supervise, and coordinate assigned activities to meet functional objectives.
* Train and develop assigned staff to improve technical proficiency, analytics capability, and section performance.
* Implement approved policies, processes, systems, standards, and procedures in line with company and international standards.
* Comply with HSE policies, controls, sustainability guidelines, applicable legislation, and ADNOC Code of Practices.
* Provide inputs for section MIS reports, progress reports, management updates, and performance summaries.
Ideal Profile
* Bachelor’s Degree in Engineering, Artificial Intelligence, Robotics, Petroleum, Computer Science, Data Science, or an equivalent discipline.
* Minimum 10 years of experience in large-scale data science, data analytics, artificial intelligence, and software development within the Oil and Energy sector.
* Strong understanding of natural language processing, machine learning, artificial neural networks, deep learning, statistical modeling, and predictive analytics.
* Strong hands-on experience with machine learning APIs and computational packages such as TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, and statsmodels.
* Strong knowledge of Python, SQL, and R.
* Familiarity with Scala, Java, C, C++, version control, and Matlab is an advantage.
* Experience using business intelligence and visualization tools such as Spotfire, Tableau, or similar platforms.
* Experience with data mining, visualization, data preparation, preprocessing, feature engineering, feature selection, model training, classification, and regression.
* Experience with supervised and unsupervised machine learning algorithms.
* Strong background in data capture, aggregation, collation, manipulation, and analysis of large datasets.
* Experience with big data frameworks such as Hadoop and Spark.
* Practical ability to work with real-time data, sensor data, maintenance logs, datasheets, images, voice, text, metering data, and other oil and gas data sources.
* Strong analytical mindset with solid mathematics, statistics, business insight, and problem-solving capability.
* Experience building AI roadmaps, proof of concepts, pilot projects, decision support systems, and scalable production-level analytics applications.
* Ability to work with discipline engineers, petroleum engineers, drilling teams, production teams, operations excellence groups, IT representatives, procurement teams, vendors, and consultants.
* Excellent communication, presentation, facilitation, and stakeholder engagement skills.
* Proficient in English with the ability to explain technical AI and analytics concepts to business and engineering audiences.
* International certifications in project management, process improvement, standardization, or technology implementation are advantageous.
Skills Set
* Digital oilfields
* Artificial intelligence
* Data science
* Data analytics
* Machine learning
* Deep learning
* Big data analytics
* Predictive modeling
* Statistical modeling
* Natural language processing
* Artificial neural networks
* Time series prediction
* Data mining
* Data visualization
* Decision support systems
* AI strategy
* AI guidelines
* Digital oilfield strategy
* Offshore analytics
* Production optimization analytics
* Exploration analytics
* Development analytics
* Drilling analytics
* Sensor data analytics
* Real-time data processing
* Structured data
* Unstructured data
* Feature engineering
* Feature selection
* Model training
* Classification
* Regression
* Supervised learning
* Unsupervised learning
* TensorFlow
* Theano
* PyTorch
* Keras
* Scikit-Learn
* NumPy
* SciPy
* Pandas
* statsmodels
* Python
* SQL
* R
* Scala
* Java
* C
* C++
* Matlab
* Hadoop
* Spark
* Spotfire
* Tableau
* Proof of concept development
* Pilot project deployment
* Data platform design
* Technology benchmarking
* Vendor evaluation
* Technical workshops
* Stakeholder engagement
* MIS reporting
* HSE compliance
* ADNOC Code of Practices
Why Join Us
This opportunity is ideal for an experienced AI and data science professional who wants to drive digital oilfield transformation in Abu Dhabi Emirate, United Arab Emirates. The role offers exposure to advanced analytics, offshore production intelligence, AI strategy, big data platforms, predictive models, operational excellence, and cross-functional digital transformation within the Oil and Energy sector. It is a strong career step for someone who can combine technical AI depth, oil and gas domain knowledge, real-time data insight, and scalable solution delivery to improve safety, recovery, efficiency, and business performance.
About the Company
ADNOC Group is a leading energy company headquartered in Abu Dhabi, United Arab Emirates, with operations across the full oil and gas value chain. The group plays a major role in energy production, digital transformation, industrial development, and long-term economic growth for the UAE. Through its offshore, operations excellence, research, digital, and technology functions, ADNOC Group offers professionals the opportunity to contribute to advanced Oil and Energy programs where artificial intelligence, data analytics, digital oilfields, operational safety, and production optimization are essential to future-ready performance.
