Specialist, Digital Emerging Technologies (Data Scientist / IOT) - ADNOC Offshore

Develop and support implementation of strategies & plans for Digital Oilfields activities in line with Company\u2019s objectives and priorities, to enhance oil recovery, achieve operational excellence and promote safer operations. Develop and maintain the DOF Strategy and benchmarks against ADNOC Group of Companies. Design, implement and maintain ADNOC\u2019s Offshore the technical artificial intelligence strategy and data analytics framework in order to model complex ADNOC Offshore problems and finding opportunities by solving business related issues. Work with real-time data and perform big data mining while realizing the insights and identifying opportunities through the use of algorithms, statistical models and visualization techniques Develop and maintain ADNOC\u2019s Offshore artificial intelligence strategy for the core business and technical domains related to exploration, development and production Develop and maintain ADNOC\u2019s offshore artificial intelligence guidelines document to provide general guidance and state the minimum requirements for technical departments and projects. Work closely with discipline engineers and subject matter expertise and others in order to produce systems that utilize artificial intelligence and capable of adapting or changing based on adding data. Conduct brain storming sessions and technical workshops to identify opportunities to be assessed and prioritized, which can be solved or improved by implementing artificial intelligence tools. Conduct regular market surveys and be aware of different technological announcements (advancements) related to artificial intelligence and data science. Compare the top ranked technologies by Garner\u2019s and others and evaluate the technology functionality related to oil & gas industry. Develop scalable tools leveraging deep learning models to solve business problems in areas such as voice recognition, natural language processing and time series predictions. Suggest, collect and generate requirements. Create an effective roadmap towards the deployment of a production level artificial intelligence application. A data scientist capable to model complex problems while realizing ADNOC\u2019s offshore insights and identifying opportunities through the use of algorithms, statistical models, data mining and visualization techniques. Recommend ongoing improvements to methods and algorithms that lead to findings, including new information. Provide business metrics for the overall project to reflect improvements by periodic monitoring over multiple iterations. Conduct workshops and session to help the technical departments understand the principles and math behind the process to drive organizational buy-in and to build multi discipline teams that are capable to define, model and solve problems related to their domains. Design and launch innovative and complex analytic models and lead the development of big data capabilities and utilization as well as the coordination of cross-functional analytic initiatives. Work with different data types (sensors data, maintenance logs, datasheets, images, etc) to build, validate and maintain predictive models Educate the organization both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results. Conduct scoping session, workshops and liaise with technical departments to identify matters to be analyzed using appropriate data and appropriate analysis tools. Provide on-going tracking and monitoring of performance of decision support systems and provide algorithmic statistical models as a core. Conduct potential POCs, share the finding internally and identify opportunities to deploy pilot projects Design and develop a scalable data analytics platform and solutions. Assess, benchmark and select data analytics technologies to be added to the big data platforms Provide guidance and mentor developers regarding data analytics. Liaise with ADNOC to build and mentor a new team of Data Scientists Identify what data is available and relevant, including internal and external data sources, leveraging and automating new data collection processes Support in the application of patterns and variations in the volume, speed, variety and other characteristics of data supporting the data analytics initiative Capture structured and unstructured data (e.g., images, voice, text, or metering data) required to build models related to oil and gas business. Provide input for preparation of the Team / Department budgets and assist in the implementation of the approved Budget and work plans to deliver team objectives. Investigate and highlight any significant variances to support effective performance and cost control Contribute to the achievement of the approved Performance Objectives for the Team / Department in line with the Company Performance framework. Design and implement new tools and techniques to improve the quality and efficiency of op

Develop and support implementation of strategies and plans for Digital Oilfields activities to enhance recovery, operational excellence, and safer operations. Develop and maintain the DOF Strategy and benchmarks; design, implement, and maintain offshore AI strategy and data analytics framework to model complex problems and identify opportunities. Work with real-time data and perform big data mining to derive insights using algorithms, statistical models, and visualization. Develop AI guidelines and ensure minimum requirements for technical departments and projects. Collaborate with discipline engineers and subject matter experts to build AI-enabled systems adaptable to new data. Conduct brainstorming sessions and technical workshops to identify opportunities solvable by AI tools. Monitor market trends in AI and data science; evaluate technologies for oil & gas applicability. Develop scalable tools leveraging deep learning for voice recognition, NLP, and time series predictions. Gather and translate requirements; create roadmaps for deployment of production-level AI apps. Model complex problems to derive insights and opportunities with algorithms and data mining. Provide ongoing methodological improvements and business metrics across iterations. Conduct workshops to build organizational understanding of methods and foster cross-disciplinary teams. Design and launch complex analytic models; lead development of big data capabilities and cross-functional analytics initiatives. Handle diverse data types (sensors, maintenance logs, datasheets, images) to build, validate, and maintain predictive models. Educate IT and business teams on new approaches and statistical validation. Conduct scoping sessions, workshops, and liaise with departments to identify data-driven analysis needs. Track performance of decision-support systems and provide core algorithmic models. Conduct POCs, share findings, and identify pilot deployment opportunities. Design and develop scalable data analytics platforms; assess and select technologies for big data platforms. Mentor developers on data analytics; liaise with ADNOC to build and mentor a new Data Scientist team. Identify relevant data sources, automate data collection where possible. Support data patterns and variations in data volume, speed, and variety. Capture structured and unstructured data to support model building. Contribute to budget inputs and assist in implementing approved plans. Investigate variances to support performance and cost control. Contribute to achieving department performance objectives within the company framework. Design and implement new tools and techniques to improve quality and efficiency of operations.