Join EY to build a career defined by global scale, inclusive culture, and cutting-edge technology. We are seeking a hands-on Principal Data Scientist to tackle complex modeling challenges within the Oil & Gas sector. This role involves translating operational challenges into scientific approaches, developing critical modeling components, and defining the evidence needed for reliable deployment across various operational assets.

Key responsibilities include formulating operational problems as predictive, diagnostic, causal, or prescriptive tasks, assessing data sufficiency, and selecting appropriate statistical and machine learning approaches. You will develop methods for multivariate forecasting, state estimation, and degradation modeling, while integrating learned models with engineering equations. Specific upstream and downstream applications include production forecasting, well surveillance, product-quality prediction, yield modeling, and process optimization. Ensuring model assurance, generalization, and adherence to technical standards are also crucial.

Candidates must possess a degree in a relevant engineering, scientific, or quantitative discipline and have substantial hands-on experience developing and deploying Oil & Gas analytical solutions. Advanced expertise in at least one relevant applied modeling specialization and strong foundations in statistics, machine learning, mathematical modeling, and uncertainty assessment are required. Proficiency in Python and SQL, along with experience integrating engineering knowledge and conducting reproducible experimentation, is essential. The ability to defend technical decisions with quantitative evidence and clearly communicate assumptions and limitations is also a key requirement.