Reservoir Engineer, Data Science

🕒 April 3

⛰️ Colorado – Remote

⛰️ Colorado – Remote

💵 $105k - $185k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📊 Data Scientist

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Fervo Energy

WebsiteLinkedInAll Job Openings

51 - 200 employees

Fervo Energy provides 24/7 carbon-free energy through the development of next-generation geothermal power. Fervo’s mission is to leverage innovation in geoscience to accelerate the world’s transition to sustainable energy. Geothermal has a major role to play in the future electric grid, and Fervo’s key advancements in drilling and subsurface analytics bring a full suite of modern technology to make geothermal cost competitive. For more information, please visit www.fervoenergy.com.

📋 Description

• Build, update, and maintain reservoir simulation and analytical models to support forecasting, development planning, and optimization • Apply data science and machine learning techniques to reservoir characterization, production forecasting, and anomaly detection • Support history matching, sensitivity analyses, and scenario evaluations • Develop and maintain Python-based workflows, scripts, and tools to automate subsurface analyses and improve data quality • Integrate geological, petrophysical, stimulation, and operational data into reservoir studies in collaboration with cross-functional teams • Clearly communicate technical results through visualizations, presentations, and written reports • Stay current with emerging tools and best practices in reservoir engineering, analytics, and AI

🎯 Requirements

• B.S. in Engineering (Petroleum, Mechanical, Chemical, or related discipline) • 2+ years of experience in reservoir engineering, data science, or a related technical field; a PhD may be considered in lieu of industry experience • Strong fundamentals in reservoir engineering, including fluid flow in porous media, pressure transient analysis, material balance, and production/injection performance analysis • Experience with reservoir modeling and simulation (numerical simulators, decline analysis, forecasting tools) • Proficiency in analyzing subsurface datasets, including pressure, rate, temperature, and geologic data • Working knowledge of Python and scientific libraries (NumPy, Pandas, SciPy) or similar analytical environments • Experience applying statistical analysis, data-driven modeling, or machine learning techniques to subsurface or production data • Ability to manage and integrate large, multi-disciplinary datasets • Strong problem-solving skills with the ability to translate technical findings into actionable insights • Excellent written and verbal communication skills

🏖️ Benefits

• medical • dental • vision • life • short-term and long-term disability • flexible paid time off • paid parental leave • incentive stock options program • bonus incentive program • 401(k) plan with an employer match