Head of Geothermal Reservoir Modeling & Forecasting

Ormat Technologies; Reno (NV); On-site; USD 180,000 - 240,000; Full time

Job summary

Ormat Technologies seeks a Manager of Reservoir Engineering Modeling to lead the numerical modeling team across operating fields, greenfield developments, and expansion projects. You will own development, calibration, and application of reservoir models to support long‑term generation forecasts and asset value.

The role emphasizes technical leadership, data‑driven decision making, and the use of modern computational tools, including Python or MATLAB, with a focus on uncertainty quantification

Qualifications

• Minimum 7 years of reservoir engineering experience with numerical modeling.
• Geothermal reservoir experience strongly preferred.
• Proven ability to lead technical teams.
• Strong in history matching, forecasting, and evaluation of development scenarios.
• Ability to translate reservoir models into business recommendations.
• Proficiency in Python or MATLAB; ML/AI tools a plus.

Responsibilities

• Lead the numerical modeling team across fields and projects.
• Develop, calibrate, and apply reservoir models.
• Establish standards, QA, peer review for modeling.
• Translate forecasts into development strategies and budgets.
• Communicate uncertainty and offer data-driven recommendations.
• Represent Ormat with JV partners and external stakeholders.

Skills

Reservoir modeling

Team leadership

History matching

Forecasting

Data analytics

Education

Master’s degree in reservoir, petroleum, or geothermal engineering

Tools

Python

MATLAB

Job description

Ormat Technologies seeks a Manager of Reservoir Engineering Modeling to lead the numerical modeling team across operating fields, greenfield developments, and expansion projects. You will own development, calibration, and application of reservoir models to support long‑term generation forecasts and asset value.

The role emphasizes technical leadership, data‑driven decision making, and the use of modern computational tools, including Python or MATLAB, with a focus on uncertainty quantification