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Data Science Fall Internship 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 ...

Copart is seeking a Data Science Senior Analyst to help provide vision and commitment to key Copart ... Required Skills and Experience : * 3-5+ years of experience (relevant academic internships and ...

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

Launch your data science or technical analyst career by building AI and analytics solutions that ... Experience through internships, personal projects, research, hackathons, student organizations, or ...

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Data Science Fall Internship information

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$12

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$42

How much do data science fall internship jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for data science fall internship 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 types of projects can I expect to work on during a Data Science Fall Internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

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

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What is a Data Science Fall Internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

More about Data Science Fall Internship jobs
What cities are hiring for Data Science Fall Internship jobs? Cities with the most Data Science Fall Internship job openings:
What states have the most Data Science Fall Internship jobs? States with the most job openings for Data Science Fall Internship jobs include:
Infographic showing various Data Science Fall Internship job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Data Science intern

Data Science intern

DEUNA

San Francisco, CA

Temporary

Posted 14 days ago


Job description

About DEUNA 
 
DEUNA is a rapidly growing startup revolutionizing global commerce with ATHIA, our AI-powered orchestration and payments platform that helps large enterprises boost approval rates, reduce costs, and unlock new revenue. Built by the team behind DEUNA-the fastest-growing Commerce OS in Latin America-ATHIA combines payment intelligence, checkout optimization, and data orchestration in one powerful solution.
 
With deep integrations across 300+ PSPs and alternative payment methods, and over 20% of Mexico's digital economy running through our platform, we simplify global payments through a single integration and centralized reconciliation.
We are a rapidly growing startup expanding into the U.S. to meet the urgent needs of large retailers, marketplaces, airlines, and QSRs. Join us to shape the future of payments!
 
Visit https://www.deuna.com/ to learn more about us!

We are looking for curious, analytical, and motivated students who are eager to learn about Data Science in a fast-paced technology environment. During the internship, you will support the Data team by analyzing data, building models, developing insights, and contributing to projects that have a direct impact on our products and business.

This is an educational, unpaid internship designed to provide practical experience, mentorship, and exposure to real-world data science projects.

Key Responsibilities
  • Assist in collecting, cleaning, and preparing datasets for analysis.
  • Perform exploratory data analysis to identify trends and patterns.
  • Support the development and evaluation of machine learning models.
  • Build dashboards and visualizations to communicate business insights.
  • Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.
  • Document analyses, methodologies, and project findings.
  • Participate in team meetings, knowledge-sharing sessions, and technical discussions.
  • Learn and apply best practices in data science, experimentation, and analytics.
Qualifications Required
  • Currently pursuing a Bachelor's or Master's degree in:
    • Computer Science
    • Data Science
    • Statistics
    • Mathematics
    • Engineering
    • Economics
    • Physics
    • Or a related quantitative field.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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