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Tier-1 employer, mid-level ML role, metro location, and common Data Scientist title increase competition.
Strong ML skills transferable, but oil and gas domain preference raises industry specificity moderately.
Requires Master's/PhD and 5+ years plus specialized ML skills, making filters strict.
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Lead end-to-end delivery of AI/ML solutions including scoping, modeling, evaluation, deployment, and monitoring for oil and gas business problems.
Develop and implement advanced data science tools and models such as GenAI/NLP applications, time-series, computer vision, and commercial analytics.
Build and maintain production-ready AI/ML solutions following MLOps best practices like MLflow, CI/CD, monitoring, and data quality controls.
Master’s or Ph.D. degree in Data Science, Computer Science, IT, Engineering, Applied Math or related disciplines with minimum 7.0 GPA.
5+ years of relevant experience developing, delivering, and validating production-ready AI/ML solutions.
Proficiency in Python or R and ML frameworks such as PyTorch, TensorFlow, scikit-learn; experience in the full ML lifecycle.
Experience with statistical (classification, regression, Bayesian, time-series) and machine learning techniques (deep learning, causal analysis).
Demonstrated expertise in areas like Time Series Analysis, Computer Vision, Natural Language Processing, Generative AI, or Commercial Analytics.
Experience working with agile software engineering practices, version control (Git), and cloud data science frameworks like Azure Databricks preferred.
Domain experience in oil & gas, commercial supply chain, production systems, wells, or subsurface domains is highly valued.