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Data Science Summer Intern Jobs (NOW HIRING)

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

Completed at least 2 years of college with a focus on law, political science, public policy ... when completing data entry * Ability and confidence in communicating questions and project ...

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Data Science Summer Intern information

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$12

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$42

How much do data science summer intern jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for data science summer intern 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 does a Data Science Summer Intern do?

A Data Science Summer Intern typically works with a team of data scientists and analysts to help collect, clean, and analyze data. They may assist in building machine learning models, visualizing data, and generating reports to provide actionable insights for the organization. Interns often gain hands-on experience with programming languages like Python or R, as well as tools such as SQL and data visualization software. Their work supports larger projects and helps them develop practical skills for a career in data science.

What are the key skills and qualifications needed to thrive as a Data Science Summer Intern, and why are they important?

To thrive as a Data Science Summer Intern, you need a solid understanding of statistics, data analysis, and programming languages such as Python or R, often supported by coursework or projects in data science or related fields. Familiarity with data visualization tools (e.g., Tableau), machine learning libraries (e.g., scikit-learn), and version control systems (e.g., Git) is typically expected. Curiosity, problem-solving ability, and effective communication help interns stand out when tackling real-world data challenges and presenting findings. These skills and qualities are crucial for extracting actionable insights from data and contributing meaningfully to team projects.

How do Data Science Summer Interns typically collaborate with other team members during their internship?

Data Science Summer Interns often work closely with data scientists, analysts, and engineers as part of cross-functional project teams. They usually participate in regular meetings, share progress updates, and seek feedback from mentors or supervisors. Interns may be assigned specific tasks within larger projects, such as data cleaning, exploratory analysis, or model development, and are encouraged to ask questions and contribute ideas. This collaborative environment helps interns learn from experienced professionals while developing both technical and communication skills.

What is the difference between Data Science Summer Intern vs Data Analyst Summer Intern?

AspectData Science Summer InternData Analyst Summer Intern
Required CredentialsTypically pursuing or holding a degree in Data Science, Computer Science, or related fieldsUsually pursuing or holding a degree in Statistics, Business, or related fields
Work EnvironmentTech companies, startups, research labs with focus on data modeling and machine learningBusiness firms, marketing agencies, finance companies focusing on data reporting and analysis
Employer & Industry UsageCommon in tech, finance, healthcare industriesPrevalent in retail, finance, consulting sectors

While both roles involve working with data, a Data Science Summer Intern typically focuses on building models, machine learning, and advanced analytics, whereas a Data Analyst Summer Intern concentrates on data reporting, visualization, and insights. The choice depends on your career interests in technical modeling versus data interpretation.

More about Data Science Summer Intern jobs
What cities are hiring for Data Science Summer Intern jobs? Cities with the most Data Science Summer Intern job openings:
What are the most commonly searched types of Data Science Summer jobs? The most popular types of Data Science Summer jobs are:
What states have the most Data Science Summer Intern jobs? States with the most job openings for Data Science Summer Intern jobs include:
Infographic showing various Data Science Summer Intern job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Applied Data Science Intern

Evolver

Palo Alto, CA โ€ข On-site

Full-time, Internship

Re-posted 11 days ago


Job description

Applied Data Science Summer Internship
About Us:
Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In just 1.5 years, the company has grown from 0 to nearly 100 employees, bringing together an exceptional team of technologists, researchers, and industry experts. Founders includes former executives from some of the world's top organizations, including the former Global CTO and Global Board Member of Ernst and Young and the former VP of AI from Microsoft, alongside senior leaders from other major global enterprises. The team includes multiple PhDs and a strong concentration of employees with advanced degrees from leading universities. This in-person internship offers a small cohort of students the opportunity to work directly alongside experienced operators and AI experts while gaining hands-on exposure to using the latest innovations in data science applications at a frontier startup environment.
Program Details:
Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases.
This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment.
  • Duration: 10 weeks (full-time), June through Early August.
  • Competitive Compensation: Tailored to your experience and skill set.
  • Format: Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
  • Cohort Size: Small and mentorship-focused
  • Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Role Details:
Interns will contribute to real data innovation projects involving:
  • Data analysis and machine learning pipelines
  • AI agents, retrieval systems, and evaluation frameworks
  • Enterprise AI integration and deployment tooling
  • Product prototyping and applied research
  • Automation systems for large-scale organizational use
  • Real world enterprise use cases of graph theory
  • Gain direct exposure to Fortune 500 clients
  • Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.

Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.
Mentorship & Learning
Interns will work closely with experienced staff and technical mentors with expertise in:
  • Computer Science
  • Data Science & Analytics
  • Applied AI & Machine Learning
  • Enterprise Infrastructure
  • Scalable AI Deployment
  • Risk and Compliance Frameworks
  • Tax and Audit

The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:
  • Daily in person technical collaboration
  • Rapid learning and iteration
  • Exposure to real deployment challenges
  • Cross-disciplinary problem solving
  • Professional development in AI engineering and enterprise systems

Who Should Apply:
We welcome applications from:
  • Graduate students with a record of excellence
  • Exceptional advanced undergraduates

All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.
Strong candidates typically demonstrate:
  • Programming experience
  • Curiosity about AI systems and emerging technologies
  • Initiative, creativity, and strong problem-solving ability
  • Prior technical, research, or project experience

You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.