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Data Science Internship Biotech 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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How much do data science internship biotech jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for data science internship biotech in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is a data science internship in biotech?

A Data Science Internship in Biotech is a temporary, supervised position where interns apply data science techniques to biological and medical data within a biotechnology company. Interns typically work on real-world projects involving data analysis, machine learning, or bioinformatics to help solve challenges in drug discovery, genomics, or healthcare. The internship provides practical experience, helps interns develop valuable technical and domain-specific skills, and can lead to future job opportunities in the biotech industry.

What types of projects does a data science intern typically work on in biotech?

Data Science Interns in biotech companies often contribute to projects involving the analysis of large-scale biological data, such as genomic sequences or clinical trial results. They might work on building predictive models to assist with drug discovery, automating data processing workflows, or visualizing complex datasets for research teams. Interns regularly collaborate with biologists, chemists, and other data scientists, gaining exposure to interdisciplinary teamwork and the unique challenges of working with sensitive, high-dimensional biomedical data.

What are the key skills and qualifications needed to thrive as a data science intern in biotech, and why are they important?

A Data Science Intern in Biotech should have a solid understanding of statistics, data analysis, and programming (especially Python or R), typically supported by coursework in computer science, biology, or related fields. Familiarity with data visualization tools, bioinformatics databases, and platforms like Jupyter Notebook or Tableau is highly beneficial. Strong problem-solving abilities, curiosity, and effective communication help interns translate complex data into actionable insights for interdisciplinary teams. These skills enable interns to contribute meaningfully to biotech research by extracting and communicating value from large, complex biological datasets.

What is the difference between Data Science Internship Biotech vs Data Analyst?

AspectData Science Internship BiotechData Analyst
Required CredentialsTypically pursuing or completed a degree in Data Science, Biotechnology, or related fieldsUsually holds a degree in Statistics, Mathematics, or related fields
Work EnvironmentBiotech companies, research labs, pharmaceutical firmsVarious industries including finance, healthcare, marketing
Industry UsageApplied to biotech research, drug development, genomicsApplied to business insights, reporting, and decision-making

While both roles involve data analysis skills, a Data Science Internship in Biotech focuses on applying data science techniques to biotech-specific problems, often requiring knowledge of biology or biotech tools. A Data Analyst generally works across industries, emphasizing data reporting and visualization. The internship provides hands-on experience in biotech settings, whereas a Data Analyst role is broader and industry-agnostic.

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Data Science Internship Biotech jobs near you
Infographic showing various Data Science Internship Biotech job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

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