Advanced Data Scientist

Work with data scientists, data analysts, computational engineers, machine learning engineers, software developers, or business representatives across our global organization to research, develop, and deliver data science tools, models, or software for solving challenging business problems in the oil and gas industry.

Lead end-to-end delivery of AI/ML solutions: scoping, modeling, evaluation, deployment, and monitoring.

Develop GenAI/NLP applications, and/or time-series, computer vision, commercial analytics models.

Build production-ready solutions applying MLOps best practices (MLflow, CI/CD, monitoring, data quality).

Apply data science methods, machine learning tools, visualization and/or statistical techniques along with domain knowledge to generate actionable insights and provide optimized recommendations.

Expertise in one or more of the following: Time Series Analysis, Computer Vision, Natural Language Processing, Generative AI, Commercial Analytics.

Master’s or Ph.D. degree from a recognized university in one of the following disciplines: Data Science, Computer Science, IT, Chemical Engineering, Mechanical, Civil, Materials, Aerospace, Geoscience/Geophysics, Applied Math or related disciplines with a minimum GPA of 7.0.

5+ years of relevant experience in developing, delivering, and validating production-ready AI/ML solutions.

In-depth knowledge and practical experience in statistical analysis techniques (e.g., classification, regression, time-series, Bayesian techniques) and machine learning techniques (e.g., decision trees, ensemble methods, deep learning, neural networks, causal analysis).

Practical experience in the full machine learning lifecycle from problem formulation, data acquisition, data cleaning to model building and deployment at enterprise level.Proficiency in Python or R, ML frameworks (PyTorch, TensorFlow, scikit-learn) and libraries (NumPy, pandas).