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Data Science Fall Internship Jobs (NOW HIRING)

Athena LLC

Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

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Data Science Fall Internship information

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

As of Aug 22, 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 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 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 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.

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Data Science Fall Internship jobs near you
Infographic showing various Data Science Fall Internship job openings in the United States as of August 2026, with employment types broken down into 22% Internship, 22% Full Time, 52% Part Time, and 4% Contract. Highlights an 89% In-person, 4% Hybrid, and 7% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Science Intern

Athenago

Wilmington, DE

Part-time

Re-posted 15 days ago

Job description

At Athena, we empower possibility through transformative delegation. True leaders reflect on what they want and map the path to get there. We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ongoing support throughout the journey. The result: 10x more leverage, more time, and a greater impact.

We are on a mission to build the best delegation platform in the world, leveraging Human+AI to provide superior experiences for delegating complex tasks.

Role Overview

The Data Science Intern will help us to understand the performance of Executive Partners (XPs) and build advanced matching models to evaluate Athena's Executive Partners (XPs) and clients, delivering tailored recommendations based on robust data insights. You will actively contribute to enhancing our delegation platform by leveraging predictive modeling, data analytics, and optimization techniques.

Responsibilities

  • Build and refine matching models to evaluate Athena's Executive Partners (XPs) and clients, ensuring optimal pairings between them based on data insights.

  • Analyze large and diverse datasets (e.g. client requirements, XP performance metrics) to uncover trends and generate actionable recommendations.

  • Collaborate closely with data science, product, and engineering teams to integrate models into production systems.

  • Present findings through clear reports, visualizations, or dashboards that inform business decisions and improve the client-XP matching process.

  • Support continuous model optimization and validation efforts.

Qualifications

  • Currently pursuing a graduate degree or senior undergraduate status in Data Science, Computer Science, Statistics, or related fields.

  • Proficiency in programming languages and data tools such as Python (with libraries like pandas, scikit-learn) and SQL for data manipulation.

  • Strong foundation in statistics and machine learning concepts (regression, classification, clustering) and familiarity with building predictive models.

  • Experience working with datasets - cleaning data, feature engineering, and using data visualization tools to present insights.

  • Excellent problem-solving abilities and attention to detail, with the ability to interpret data to make logical recommendations.

Preferred Qualifications

  • Familiarity with machine learning frameworks or libraries (e.g. TensorFlow, PyTorch, scikit-learn) and experience training or fine-tuning models.

  • Prior exposure to recommendation algorithms or matching systems through coursework or projects.

  • Familiarity with cloud platforms (AWS, GCP) and big data technologies (e.g., Spark, S3, Snowflake).

  • Previous internship or project experience demonstrating practical data science applications.

  • Understanding of human resource or matchmaking domains (e.g. matching candidates to roles or services to clients) is a plus.

Benefits

  • Mentorship & Training: You will receive guidance from experienced data scientists and engineers. Expect one-on-one mentorship, regular feedback, and access to learning resources to accelerate your growth.

  • Hands-On Experience: Work on real-world projects that have direct impact on Athena's services. You'll have ownership of meaningful tasks and contribute code to production-level systems, building your portfolio.

  • Inclusive Culture: Experience Athena's collaborative and inclusive culture firsthand. Interns participate in team meetings, social events, and all company perks - you'll be treated as an equal team member throughout your internship.

  • Path to Opportunities: A successful internship can pave the way to future roles at Athena.com. Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

Apply