9 Data Science Intern Resume Examples for 2025

Starting a career in data science can be tough. This article offers real examples of data science intern resumes, plus tips to make yours stronger. Learn how to highlight your skills and experience to appeal to hiring managers.

  Compiled and approved by Liz Bowen
  Last updated on See history of changes

  Next update scheduled for

At a Glance

Here's what we see in the strongest data science intern resumes.

  • Quantifiable Achievements: Best resumes show value with numbers like reduced error rates by 10%, automated 5 processes, enhanced data retrieval speed by 20%, and analyzed 1,000+ data sets.

  • Relevant Technical Skills: You should include skills from the job description. Examples are Python, SQL, machine learning, R programming, and data visualization. Pick the ones you know.

  • Industry Tools And Software: Familiarity with tools is a must. Add phrases like proficient in Tableau or experienced with TensorFlow to show you know industry software.

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Positioning education on your resume

As a hiring manager, you must show your education clearly on your resume. Data science intern candidates are often in the early stages of their careers. If you are a student or a recent graduate, place your education section at the top. It will help hiring managers see your relevant academic background quickly. Focus on your degree subjects, any special projects, or statistics and programming courses that are essential for data science roles.

If you have completed a significant form of further education like a data science bootcamp or a related master's degree, this information should lead your resume. This tells employers that your recent training is your main qualification. As a data science intern, you want to highlight your understanding of data analysis, machine learning, or any specific tools like Python or R that you have studied. This shows you are ready to apply what you have learned in a practical setting.

Showcase relevant projects

For a data science role, showcasing relevant projects can set you apart. Include details about projects that involve data analysis, machine learning, or programming. Mention specific tools and techniques you used.

Consider creating a portfolio of your best work. This can include links to projects on platforms like GitHub or personal websites.

Keep your resume concise

As an intern in data science, you should aim for a resume that is one page long. You are likely starting out or have limited professional experience. Show you can prioritize by including only the most relevant information. Focus on your strongest projects, technical skills, and any academic or extracurricular activities that highlight your abilities in data handling and analysis.

Do not worry about a one-page limit making you seem inexperienced. It shows you understand the importance of clear and relevant detail. Make sure the skills and experiences you choose to include reflect your understanding of data science tools and concepts that are vital in the field, such as programming languages, data visualization, and statistical analysis.

Highlight technical skills

Technical skills are very important in data science roles. Make sure to list skills such as Python, R, SQL, and machine learning techniques. Mention any software or tools you're comfortable with like TensorFlow or Tableau.

Include any relevant certifications or courses you've completed. This shows your commitment to learning and growth in the field.

Understand resume screeners

When you apply for a data science internship, your resume may first be read by a computer program called an Applicant Tracking System (ATS). This system looks for certain words and phrases to decide if your resume is a good match for the job.

You need to make sure your resume works well with these systems. Here are two ways to do this:

  • Include keywords from the job description. Look for skills and tools mentioned, like 'Python' or 'data analysis', and put these words in your resume.
  • Use a simple format with clear headings. The ATS can read your resume better this way. For example, have sections titled 'education', 'experience', and 'skills'.

Match your skills to the job

You want your resume to show you are a good fit for a data science internship. Look at the job description. Use the same words they use for skills and experiences if you have them. This can help your resume get noticed.

  • List software you know that is important for data science. For example, include Python, R, or SQL if you have used these.
  • Show the projects where you used data to find important information. Use phrases like analyzed large datasets to identify key trends.
  • If you have done any work with data before, even in school, include it. Talk about what you did with the data and what tools you used.

Essential skills for data science roles

When you apply for a data science internship, your resume should highlight the technical skills that show you can handle data well. Here's a focused list of skills to consider:

  • Python
  • R
  • SQL
  • Machine learning
  • Data visualization
  • Statistical analysis
  • Hadoop
  • Tableau
  • TensorFlow
  • Deep learning

Choose skills that match the job you want. If you like working with big data, Hadoop is key. If you're into making data easy to understand, focus on Data visualization and tools like Tableau. Put these skills in a separate section on your resume so they are easy to find.

Remember, you don't need every skill listed. Start with what you know best. Many companies use systems that scan resumes for these skills. These are called Applicant Tracking Systems (ATS). Make sure to list your skills where they can be easily seen to pass the ATS check.

Showcase leadership in your experience

As a hiring manager, I know the value of leadership in the workplace. When you apply for a data science internship, you should show any leadership roles or promotions you've had. Even if you are new to the field, think about times when you've guided others or taken charge of a project.

Here are ways to show leadership experience:

  • Include any positions where you had to lead a group, like being a project manager for a class assignment or a team leader in a club.
  • Describe tasks where you were in charge, such as organizing a data analysis project or mentoring new members in a student organization.

Also, highlight any promotions:

  • List any roles where you started as a team member and became a team lead or project coordinator.
  • Share examples of times when your responsibilities increased, like going from helping with data collection to analyzing the data.
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