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Overnight Data Science Internships Jobs (NOW HIRING)

Fervo Energy

Data Science Internship

Houston, TX · On-site

Description Internship Overview You won't be running coffee orders or shuffling paperwork this ... As a Data Scientist Intern, you'll join Fervo's Data Science team to help build models and analyses ...

Fervo Energy Company

Data Science Internship

Houston, TX · On-site

Internship Overview You won't be running coffee orders or shuffling paperwork this summer. At Fervo ... As a Data Scientist Intern, you'll join Fervo's Data Science team to help build models and analyses ...

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Overnight Data Science Internships information

What is the difference between Overnight Data Science Internships vs Data Science Internships?

AspectOvernight Data Science InternshipsData Science Internships
Work HoursTypically involve overnight shifts, often 10-12 hoursUsually standard daytime hours, 8 hours
Work EnvironmentRemote or on-site, with overnight schedulingPrimarily daytime, office or remote
CredentialsRequired skills in data analysis, programming, and possibly some certificationsSimilar credentials, often requiring coursework or certifications in data science
Industry UsageCommon in 24/7 operations like tech, finance, or healthcareWidespread across various industries including tech, finance, healthcare

Overnight Data Science Internships focus on overnight shifts, suitable for industries with 24/7 operations, while standard Data Science Internships follow regular hours. Both require similar skills and credentials, but the scheduling differs significantly.

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Overnight Data Science Internships jobs near you

Data Science Internship

Houston, TX • On-site

Fervo Energy
Clean Energy Semiconductors Manufacturing • 11 - 50 employees
Learn more about Fervo Energyexternal

Full-time, Internship

Posted 10 days ago

Job description

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 

Apply