Data Analyst Resume Tips: What to Include

Key takeaways

A data analyst resume demonstrates you have the skills, experience and qualifications needed to get the job done. At a glance, here's what you need to know about data anlysis resumes:

• Data analyst jobs are growing to become a high-demand occupation across the United States. Job growth projections from 2024 to 2034 are 21 percent [1]. 

• In this role, you gather valuable insights to help businesses make informed decisions in areas such as price modeling, marketing, and business operations. 

• Effective resumes highlight relevant skills, experience, and credentials while also speaking to your suitability for the specific position to which you're applying.

Read on to explore resume writing tips and what to include in this handy guide. Afterward, if you want to build your data analytics skills, consider enrolling in the Google Data Analytics Professional Certificate.

What types of data analyst jobs exist?

Data analysts fill all kinds of data-related positions, including business intelligence analysts, computer systems analysts, database administrators, and data modelers. This creates opportunities to find data analyst jobs that fit your skill set. For example, if you have experience developing visualizations of data points and their relationships, you could be a great fit for data modeling positions. 

The following list demonstrates the variety of fields you can work in as a data analyst:

• Data engineer

• Database administrator

• Financial analyst

• Logistics analyst

• Management analyst

• Market analyst

• Medical data analyst

• Project data analyst

• Regulatory data analysts

• SQL developer

• Systems analyst

How should you construct a data analyst resume?

Your experience in data analytics should determine how you construct your resume, as someone entering the field tends to have less hands-on work experience than someone pursuing a senior-level role.

For example, suppose you’re seeking an entry-level role and have limited experience. In that case, you might focus instead on showcasing how you’ve solved problems and overcome challenges in internships, volunteer experience, or other roles. A more experienced data analyst will want to demonstrate their impact and technical expertise, highlighting specific examples from their past work. 

To effectively present your qualifications, it's essential to understand the key components of a data analyst resume and what to include in each section. Consider the following critical sections of a resume:

Resume header

Regardless of your experience level, this section of a data analytics resume should always include your name and contact information. When listing your email, it’s important to have a professional email, such as variations of your name, without numbers or nicknames. You can also choose to include a URL to your LinkedIn profile. 

Education, experience, and skills

When listing your data analyst education, begin with your most recent program and include the major of your studies. You can add any notable honors or awards you received during your time in school, as well as relevant coursework.

Your experience section is a critical component of your resume because the employer will want to know what you’ve done in the past that makes you a good fit for their position. If you’re applying to your first data analyst role, it’s reasonable to have limited experience. You can still share internship or research experience from your time in school. Even volunteer work can be beneficial in demonstrating the valuable experience you can offer. When highlighting your work, focus on using action verbs to show your impact and accomplishments. 

Consider using a list format to include your skills on your resume. Only add relevant skills that you can demonstrate proficiency with. Before adding them, delve deeper into the company and position to ensure you include the skills you have that the employer is looking for. 

Read more: How to Make a Resume: Your resume Writing Guide

What type of relevant experience is applicable?

It can be challenging for recent graduates and those looking to make a career change over to data analytics to determine whether they have enough relevant experience to qualify for a position. However, it’s helpful to understand that job descriptions include details of what employers would like to have in their prospective candidates, so if you meet the majority of the requirements, it’s still worth applying. 

Focus on the specific skills that apply to data analytics. Projects and internships where you’ve worked with data are worth noting. Completing a certification or earning a Professional Certificate is a great way for anyone to gain demonstrable skills specific to data analytics, regardless of your degree or previous work experience.

Requirements for data analyst positions

Data analysis positions typically require you to have completed a bachelor’s degree in a relevant field, such as computer science or data science. However, as previously mentioned, certifications are an option for developing the necessary skills to fill the gap if you don’t have a relevant degree or experience. 

Hiring managers frequently look for the following skills and areas of expertise as they review resumes of data analyst candidates:

• Critical thinking

• Problem-solving

• Math and statistics

• Communication

• Programming

• Data visualization

• Machine learning

• Generative AI

How AI is transforming data analytics

Generative AI tools like Claude, ChatGPT, and Microsoft Copilot are increasingly being used by data professionals to complete their day-to-day tasks. Some common use cases include to clean, organize, and analyze data sets. Stay up with these transformations by building you own AI skills today.

Read more: AI in Analytics: Examples, Benefits, and Real-World Use Cases

Jobs that require data analyst education or experience

You can apply your data analyst skills in various roles, including data architect, machine learning engineer, insurance underwriting analyst, and more. Although you may start in an entry-level position, you can progress to senior data analyst positions and analytics management roles or choose to specialize in specific data analytics industries and areas. Consider the following careers related to the role of data analyst:

• Data scientist

• Business analyst

• Data security analyst

• Health care analyst

• Systems analyst

• Financial analyst

• Database administrator

• SQL developer

• Data engineer

• Operations analyst

• Data warehouse architect

Industries and companies that hire data analysts

Data analysts can find employment across numerous industries. Some of the top industries hiring data analysts include health care, finance, telecommunications, transportation, entertainment, agriculture, and retail. According to data from Zippia, the following are the top ten companies when it comes to hiring data analysts [2]:

• Capgemini

• Capital One

• Bloomberg

• Robert Half

• Accenture

• Back of America

• IBM

• AT&T

• Citi

• JP Morgan Chase

Keep learning about data analytics

A strong data analysis resume is the cornerstone of your job application. Build you data skills and prepare for your next role with these resources from Coursera:

• Watch on YouTube: Why Your Data Isn't Telling a Story

• Brush up on your vocab: Data analysis Terms & Definitions

• Get ready for your interview: Data Analyst Interview Preparation Guide

With Coursera Plus, you can learn and earn credentials at your own pace from over 350 leading companies and universities. With a monthly or annual subscription, you’ll gain access to over 10,000 programs—just check the course page to confirm your selection is included.