Data Analyst Resume Tips: What to Include

Data analyst jobs are growing to become a high-demand occupation across the United States. Job growth projections from 2022 to 2032 are 23 percent, equating to over 10,000 openings yearly [1]. 

Technological growth has driven demand as it increases the amount of accessible data. As companies increasingly look to maximize their use of all this data, they turn to data analysts who can help them make sense of it. In this role, you gather valuable insights to help businesses make informed decisions in areas such as price modeling, marketing, and business operations. 

Data analyst positions are wide-ranging, so it makes sense to consider the type of data analyst role you’re interested in before using this information to craft a resume that gets you noticed. Read on to explore data analyst resume writing tips and what to include in this handy guide.

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. 

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. For example, you can earn a Google Data Analytics Professional Certificate in a matter of months, allowing you to obtain job-ready skills employers are looking for. 

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

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 in 2024 [2]:

• Capgemini

• Capital One

• Bloomberg

• Robert Half

• Accenture

• Back of America

• IBM

• AT&T

• Citi

• JP Morgan Chase

Next steps

Gaining relevant work experience and specialized education can open multiple avenues for career advancement in data analysis, a rapidly expanding field across various industries. By honing your skills and tailoring your resume to highlight these qualifications, you can effectively position yourself for the numerous opportunities in this high-demand profession. 

On Coursera, you can find highly-rated courses to help you start your career as a data analyst. For example, the Google Data Analytics Professional Certificate can help you go from beginner-level to job-ready in as little as six months. 

Additionally, Excel Skills for Data Analytics and Visualization from Macquarie University is an excellent way to develop in-demand skills for industry experts to master valuable data visualization skills. You can learn more about analytics processes and different data roles with Introduction to Data Analytics from IBM. This course covers essential concepts such as data structures and sources.