Direct message the job poster from 10Pearls Role Overview: As a Lead Data Scientist in the oil and gas sector, you will spearhead advanced analytics initiatives, leveraging data-driven insights to optimise exploration, production, and operational efficiency. Your role involves building predictive models, deploying machine learning algorithms, and leading a team to solve complex challenges unique to the industry. Technical Responsibilities: 1. Data Strategy and Management: • Define and implement data strategies to support exploration, drilling, and production business goals. • Oversee data collection, cleaning, and integration from diverse sources (e.g., seismic, production logs, IoT sensors, SCADA systems). • Ensure data accuracy, consistency, and security while adhering to industry compliance standards. 2. Model Development and Deployment: • Design and implement advanced machine learning models (e.g., predictive maintenance, reservoir simulations, production optimisation). • Develop algorithms for seismic data interpretation, reservoir characterisation, and well-performance forecasting. • Optimize workflows using natural language processing (NLP) for unstructured data, such as drilling reports and maintenance logs. 3. Advanced Analytics: • Conduct exploratory data analysis (EDA) to identify trends, anomalies, and optimisation opportunities. • Utilize geospatial analysis and geostatistical techniques to interpret geological and geophysical data. • Implement real-time data analytics for drilling, well monitoring, and production enhancement. 4. Technology Leadership: • Lead the adoption of cloud-based data platforms (e.g., Azure, AWS, Google Cloud) for scalable computation. • Stay updated on emerging technologies for oil and gas applications, such as edge computing, digital twins, and advanced AI. • Drive automation of repetitive tasks using advanced scripting and machine learning pipelines. 5. Team Collaboration and Leadership: • Mentor junior data scientists and engineers, fostering a culture of innovation and excellence. • Collaborate with engineers, geophysicists, and reservoir managers to translate business challenges into data science solutions. • Communicate technical findings to non-technical stakeholders through visualisations and reports. 6. Optimization and Decision Support: • Develop optimisation models for energy efficiency, cost reduction, and supply chain logistics. • Enhance drilling accuracy and reduce downtime through predictive analytics for equipment maintenance. • Implement risk assessment models to improve safety and compliance standards. 7. Tool and Technology Expertise: • Expertise in Python, R, MATLAB, and SQL for statistical modelling and data analysis. • Proficient in machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and big data tools (e.g., Hadoop, Spark). • Hands-on experience with visualisation tools like Power BI, Tableau, or D3.js. • Familiarity with domain-specific software like Petrel, Schlumberger, or Halliburton’s DecisionSpace. Qualifications: • Advanced degree (Master’s or PhD) in Data Science, Petroleum Engineering, Geophysics, Computer Science, or a related field. • 7+ years of experience in data science, with at least 3 years in oil and gas. • Strong understanding of petroleum systems, reservoir engineering, and upstream/downstream operations. • Demonstrated success in leading data-driven projects within the oil and gas sector. Key Skills: • Deep knowledge of machine learning, statistical modelling, and geostatistics. • Strong programming and data engineering skills. • Understanding of the oil and gas lifecycle, from exploration to production. • Excellent problem-solving and communication abilities. • Proven track record of innovation in oil and gas analyses Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries IT Services and IT Consulting Referrals increase your chances of interviewing at 10Pearls by 2x Sign in to set job alerts for “Lead Data Scientist” roles. 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