Find Data Internships

Analytics internships are booming across industries like tech, finance, healthcare, sports, and entertainment.

Companies such as TikTok, Warner Bros. Discovery, IBM, John Deere, and banks like Burke & Herbert are actively hiring interns. These roles typically involve working with data visualization tools (Power BI, Tableau), SQL, Python, and machine learning basics to help organizations make data-driven decisions.

Embrace this opportunity to transform your academic achievements into real-world expertise and set the foundation for a successful career in analytics.

Why Internships Matter

Organizations face an ever-growing influx of data, making it essential to find professionals who possess a unique blend of technical expertise—such as SQL, Python or R, and business intelligence tools—and strong communication skills to translate insights effectively.

To meet this demand, many companies are expanding their internship programs in software development, IT, and data analytics. These internships serve as valuable talent pipelines, offering a cost-effective way to identify and nurture future employees.

By approaching internships as extended interviews, organizations can observe candidates’ ability to demonstrate progress, take ownership of tasks, and adapt quickly. This strategy not only helps in assessing technical and soft skills but also builds loyalty and a deeper understanding of company culture.

Overall, well-structured internships play a crucial role in developing the skilled workforce needed to leverage data for competitive advantage.

Learning on the Job

Of all the ways to get educated, few would argue that hands-on experience is the single best method of learning. What better way to master a new skill than to experience a “day in the life.” In the 17th century, this was referred to as apprenticing. 

We now see this “old-time” approach to learning being adopted in higher education settings. In just the past couple of decades, there has been an influx of co-ops at every type of college and university.

Even 30 years ago, advanced education was confined to the classroom. In this modern world, we are seeing job training as an integral part of higher learning. 

• Internship: This is a position for a trainee or student, paid or unpaid, with the end goal of gaining work experience. It may help to satisfy a requirement for qualification. At the very least, it is a good resume builder. Internships take place in all types of industries. Check out internships across the US.
  
  
• Apprenticeship: The definition of this word has evolved over the past three hundred years. Nowadays, it refers to a course of training that takes place on the job or at the workplace. It may consist of basic training for new entrants into the job. The trainee will acquire real-world experience through working directly with one who is skilled in a given area. Check out the apprenticeships in your area.
  
  
• Cooperative work experience (CWE): Trending across college campuses, this is a program in which students have the chance to combine their formal learning with practical work experience(s). It helps new entrants to the marketplace to build upon skills and be better positioned for career advancement.
  
  
• Job shadowing: Another form of job training that takes place at the workplace, this is also referred to as an “externship.” This is where an employee shadows a colleague who has more experience. It allows for a “day in the life” of a knowledgeable professional. You can gauge what it takes to excel in this type of job with exposure day in and day out.
  
  
• Service learning: This educational approach combines classroom theory with real-life scenarios. The best part is that it is all for a good cause. With service learning, students take what they have learned in the classroom setting and put that knowledge into practice by using it in a non-profit organization. It is the smart path to solidify your understanding of a business concept.
    
  
• Credit for prior learning (CPL): It’s also worth investigating if you can earn college credit(s) for an internship. 

Internship Outcomes

Many, understandably, wonder whether they will get paid as an intern. The answer is “it depends.” 

• Paid internships: Internships, even when paid, are oftentimes modest in pay. They can be in the form of an hourly wage or a stipend. They may be part-time over the school year or full-time in the summer. The duration ranges, from a couple of months to a year or two. You don’t have to search hard to find these opportunities. They are advertised on all of the major job search sites. Go to LinkedIn, Indeed, and Chegg Skills.
  
  
• Non-paid internships: These are obviously easier to get than a paid internship. It allows you to get valuable experience and insight. Think of it as training that you don’t have to pay for. You can also view it as an inexpensive way to test the waters. Before embarking on a new educational or career path, you can gain on-the-job know-how which may help save you money and time down the road.

An internship doesn’t have to come with a salary to be worth something tangible. There are all kinds of creative ways that organizations can “pay you back.” There could be course credit, paid meals, or housing perks.  

We all want to get paid for our time. If you are in school and juggling family and/or work, it may be difficult to fit in a project that doesn’t yield direct compensation. It’s important to step back and weigh the pros and cons.

This will help you to stay focused on the big picture. An internship or any related job training can pay out in the long term. The advice here is to investigate your options. Be clear as to what the internship entails and work to find one that has been well vetted. 

A Day in the Life of an Intern

One of the pluses of serving as an intern in the realm of analytics is exposure to inter-connected departments. You may work in and around Marketing, Product, IT, Research, or any other workgroup. This allows you to experience the inner workings of your role in analytics and other branches as well.

For example, you may be able to put your hard skills to the test through coding or the use of Business Intelligence (BI) tools. Or you may get to dig deep into the data with A/B testing, interpretation of results, or data cleansing.

As an intern, you get the opportunity to see what it is like to work in corporate America. You will be exposed to an array of tools. These may include email correspondence, meetings, and collaboration with peers. Other departments may seek your assistance in dashboard building and the creation and monitoring of KPIs. 

A great way to prove your worth is to help with tasks that are not as popular, like data cleansing and technical writing. Whether you observe any number of key functions, from troubleshooting to database marketing, you will have the chance to take what you have learned from your studies and see how these fit into businesses today.

The structure of an internship really varies. Generally speaking, they are set up much in the same way that a job is, minus the overtime. As mentioned previously, the span of time can also differ. However, more often than not, it is a set number of hours, on a part-time or full-time basis. These parameters should be delineated in the job listing and certainly flushed out in the early phase of the interview. 

You should have a mentor to guide you, explain your assignment(s), and serve as the person to whom you may consult with questions or concerns. An intern is also surrounded by peers to listen in on strategies. It’s a great chance to get a feel for being a member of a work team. 

How to Find an Internship

Finding an analytics internship is part strategy, part timing, and part persistence. Instead of refreshing one or two job boards, think in channels—each with its own strengths.

1. Top-Tier Job Boards & Aggregators

These sites offer the broadest reach and are essential for initial screening. Use specific keywords like “Data Analyst Intern 2026,” “Business Intelligence Intern,” or “Quant Analyst Summer.”

• LinkedIn Jobs: Use the “Internship” filter and follow companies with robust data departments (e.g., Google, Amazon, Meta, Microsoft).
• Indeed/Glassdoor: Excellent for tracking smaller companies and local startups in your area.
• University Career Portals (e.g., Handshake): Many companies specifically target universities for their recruiting, making your school’s portal a high-value resource.
• Specialized Lists: Websites like Intern List or similar career resource pages compile comprehensive lists of major company programs as they open.

2. Direct Company Career Pages

Tech, Finance, and Consulting firms are the biggest analytics employers and often post internships on their own sites first, often with early deadlines:

• Tech: Google, Apple, Meta, Amazon, Netflix, Microsoft, NVIDIA, IBM.
• Finance/FinTech: JPMorgan Chase, Capital One, BlackRock, Stripe, Wells Fargo. (Look for “Data Science Analyst” or “Applied AI/ML Associate” programs).
• Consulting: McKinsey, BCG, Deloitte, Accenture. (Look for “Strategy & Analytics” or “Technology Intern” roles).
• Government/Research: NASA, national labs, and federal agencies often offer technical internships, including data roles (e.g., NASA’s Pathways program).

3. Networking and Referrals

• LinkedIn Networking: Search for Alumni who work at your target companies in data-related roles. Send polite, concise messages asking for an informational interview to learn about their team’s work.
• Career Fairs: Attend university and regional tech/business career fairs. This is the fastest way to get your resume directly in the hands of a recruiter and potentially secure an initial screening interview.

Internship Application Guide

Think of the application process as a funnel:

Resume → Cover Letter → Interviews

1. Quantify Your Impact Through a Resume

• Action Verbs & Quantification: Do not just list duties. Use strong action verbs and always include metrics.
  • Instead of: “Used Python to analyze customer data.”
  • Use: “Developed a Python script to clean and analyze 10,000 customer records, identifying a 15% correlation between feature usage and churn.”
• Technical Skills: Clearly list your proficiency in the core analytics stack:
  • Programming: Python (Pandas, NumPy) / R
  • Querying: SQL (a must-have; specify dialects if known: Postgres, MySQL)
  • Visualization: Tableau, Power BI, Looker Studio
  • Statistics/ML: Regression, Hypothesis Testing, Classification (if applying for Data Science)
• Projects: Dedicate a section to 2-3 projects (academic or personal). Include the objective, the tools used, and the result/insight derived.

2. Tell a Story Through a Cover Letter

Keep it one page and tailor it for the specific company/role.

• Introduction: State the exact role you’re applying for and what specifically about the company’s mission or a recent project excites you. Personalization is crucial.
• Body (1-2 Paragraphs): Expand on one or two key projects from your resume that directly align with the job requirements. Avoid repeating bullet points; tell the story of the problem, your method, and your quantified impact.
• Closing: Reiterate your enthusiasm, mention your eagerness to contribute to their team, and include a polite call to action (e.g., “I look forward to the opportunity to discuss my qualifications further”).

3. Interview Preparation

Analytics interviews test three main areas:

• Technical Skills – Include proficiency in SQL, Python, and statistics, so candidates should practice writing queries, understand statistical concepts, and be able to interpret data effectively.
• Behavioral Skills – Focus on soft skills like communication, teamwork, and cultural fit, often evaluated through questions about past experiences, best addressed using the STAR method—Situation, Task, Action, Result.
• Case Study – Evaluate a candidate’s ability to solve complex problems by analyzing data, utilizing SQL, applying statistical methods, understanding behavioral responses, and demonstrating strategic thinking. They provide insight into practical skills essential for business success in real-world scenarios.

What to Expect in the Internship

During a 10 to 12-week analytics internship, you’ll engage in meaningful, standalone projects that showcase your skills and contribute to the company’s success. These projects may include creating comprehensive KPI dashboards to track performance, analyzing customer segmentation to identify key groups, or developing predictive models to forecast future trends.

Throughout the internship, the majority of your time—approximately 50 to 70 percent—will be dedicated to data cleaning and preparing datasets for analysis, which is crucial for ensuring accurate and reliable results. Additionally, a significant portion of your efforts will involve communicating your findings clearly to stakeholders, helping inform strategic decisions. Internships in this field are typically well-compensated.

In the US, interns earn an average of around $23 per hour, with top-tier firms offering between $30 and $50 or more per hour. Many internships also offer valuable benefits, such as relocation stipends, housing allowances, and other perks that enhance your experience.

Success in the internship is often judged by the quality and impact of your projects, your proactive approach to learning, and your ability to effectively communicate insights. Demonstrating initiative, strong analytical skills, and a collaborative attitude can set you apart and open doors to future opportunities in data analytics and data science.

Frequently Asked Questions

Related Resources

• Find the Best Tech Internships
• How to Get into Analytics
• How to Find a Tech Career with Numbers
• Episode 2 Niraj Jayant
• Episode 20 with Abhijith Asok