Data Science Internship

Posted 10 Days Ago
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Houston, TX, USA
In-Office
Internship
Greentech • Energy • Utilities • Renewable Energy
The Role
Data Science Interns will explore datasets, build and validate predictive and statistical models, support machine learning projects, and communicate insights to technical and non-technical stakeholders. The role involves a 12-week project supporting drilling, operations, and commercial teams in geothermal energy. Candidates must be pursuing a graduate degree in a quantitative field and demonstrate Python and data science library proficiency.
Summary Generated by Built In

Description


Internship Overview 

You won't be running coffee orders or shuffling paperwork this summer. At Fervo, interns are handed something real: a project of your own, scoped with your manager on day one and yours to drive for the full 12 weeks. You'll work side-by-side with the teams building the next generation of geothermal energy, tackling problems that genuinely move the business forward. At the end of the summer, you'll present your work to our executive leadership team, department leads, and fellow interns, sharing real results with a real audience. This is a real seat at the table — and a real shot at what comes next. 

Position Description

Fervo Energy is developing next-generation geothermal power to deliver firm, carbon-free energy at scale, anchored by our flagship Cape Station development in Milford, Utah. As a Data Scientist Intern, you'll join Fervo's Data Science team to help build models and analyses that turn data into decisions across the business. 

You'll work alongside engineers and data scientists to explore datasets, build predictive models, and translate findings into insights that inform real decisions across drilling, operations, and commercial teams. 

Requirements

 Responsibilities 

  • Explore and analyze datasets to identify trends and opportunities 
  • Build and validate predictive models and statistical analyses 
  • Support development of machine learning models for real-world business problems 
  • Communicate findings and recommendations to technical and non-technical stakeholders 

Required Qualifications 

  • Master's or PhD candidate wrapping up within the next year — we're building a pipeline toward full-time offers 
  • Pursuing a degree in Data Science, Statistics, Computer Science, or a related quantitative field 
  • Strong written and verbal communication skills, including comfort presenting to stakeholders and leadership 
  • Eagerness to learn, take initiative, and adapt quickly to new challenges 
  • Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn) 

Preferred Qualifications 

  • Experience with machine learning frameworks (e.g., PyTorch, TensorFlow) 
  • Familiarity with SQL and data visualization tools 
  • Interest in applying data science to energy or industrial problems 

Skills Required

  • Master's or PhD candidate graduating within the next year
  • Currently pursuing a degree in Data Science, Statistics, Computer Science, or a related quantitative field
  • Strong written and verbal communication skills
  • Comfort presenting to stakeholders and leadership
  • Eagerness to learn, take initiative, and adapt quickly
  • Proficiency in Python and common data science libraries, such as Pandas, NumPy, and Scikit-learn
  • Experience with machine learning frameworks such as PyTorch or TensorFlow
  • Familiarity with SQL and data visualization tools
  • Interest in applying data science to energy or industrial problems
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The Company
175 Employees
Year Founded: 2017

What We Do

Fervo Energy is a next-generation geothermal power developer providing 24/7 carbon-free energy. The company leverages innovations in geoscience, including horizontal drilling and subsurface analytics, to make geothermal energy a dependable and affordable source of clean power. Its mission is to accelerate the global transition to sustainable energy and decarbonize the most challenging parts of the electricity sector through the development of enhanced geothermal systems.

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