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Specialist, Digital Emerging Technologies; Data Scientist/IOT
Job Description & How to Apply Below
Specialist, Digital Emerging Technologies (Data Scientist / IOT)
Develop and support the implementation of strategies and plans for Digital Oilfields activities in line with the company’s objectives, prioritising operational excellence, safer operations and enhanced oil recovery.
Key Accountabilities- Lead the Offshore artificial intelligence strategy and guidelines for the core business and technical domains.
- Collaborate with discipline engineers and subject matter experts to design AI solutions that can adapt based on new data.
- Conduct workshops and technical sessions to identify opportunities for AI‑driven improvement.
- Stay updated on AI and data science advances, evaluate technologies and recommend their application to the oil & gas industry.
- Develop scalable tools using deep learning for voice recognition, NLP and time‑series predictions.
- Design and launch complex analytic models, and build big‑data capabilities across data types including sensors, logs, and images.
- Provide ongoing monitoring of decision‑support systems, and produce performance metrics.
- Mentor data scientists and developers, and contribute to building a new data science team.
- Support budgeting and performance management for the department.
- Coordinate with senior management, IT, procurement, and external vendors for project execution.
- Bachelor’s Degree in Engineering, Artificial Intelligence, Robotics, Petroleum or equivalent.
- Minimum 10 years of experience in large‑scale data science, analytics and software development within the oil & gas industry.
- Deep knowledge of NLP, ML, ANN, and experience with Tensor Flow, PyTorch, Keras, Scikit‑Learn, Num Py, Sci Py, Pandas.
- Proficiency in R, SQL, Python; familiarity with Scala, Java, C/C++, MATLAB is an asset.
- Experience with business intelligence tools (Spotfire, Tableau) and data mining/visualisation.
- Strong background in data preparation, feature engineering, model training, supervised and unsupervised learning.
- Experience with Big Data frameworks such as Hadoop and Spark.
- Excellent analytical, communication and presentation skills; proficiency in English.
- Professional certifications in project management, process improvement or technology implementation are an added advantage.
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