Data Science SME

Location: Abu Dhabi – Onsite

Key Responsibilities

• Review and validate upstream and midstream gas supply process models, including operational and process constraints.
• Assess production forecasts for overall gas production and component-level yields (C1, C2, C3, C4, and C5+).
• Review and validate feature engineering, data quality, and model design used in Machine Learning and Deep Learning solutions.
• Evaluate AI-based production optimization approaches and identify opportunities to improve model accuracy, operational efficiency, and profitability.
• Recommend enhancements to model parameters, feature selection, constraint prioritization, and optimization strategies.
• Support production planning, scheduling, and commercial decision-making through predictive analytics and optimization solutions.
• Translate complex technical concepts and AI outputs into clear, business-focused recommendations for stakeholders.

Required Skills & Experience

• Strong expertise in Python, Machine Learning, Deep Learning, and optimization techniques.
• Hands-on experience with models such as LSTM, SARIMA, Kalman Filters, SVR, Ridge Regression, probabilistic models, and ensemble approaches.
• Strong understanding of feature engineering, model validation, overfitting prevention, and time-series forecasting.
• Experience with Linear Programming, constraint-based optimization, and production optimization methodologies.
• Ability to interpret and challenge mathematical models and optimization equations.
• Strong understanding of LNG and Oil & Gas processing operations across upstream, midstream, and LNG value chains.
• Proven ability to review hybrid AI solutions and provide SME-level recommendations to improve technical performance and business outcomes.

Preferred Experience

• 10+ years of experience in LNG, Oil & Gas, Advanced Analytics, AI/ML, or Production Optimization.
• Experience supporting digital transformation, process simulation, and AI-driven optimization initiatives within the energy sector.
• *** Only successful candidates will be contacted ***