Data Analyst Resume Guide & Tips

Crafting a strong resume in data analytics is a great way to show employers you are passionate about working with data and have the necessary experience to contribute to their organization. This article will provide an overview of what to include on your data analytics resume, what not to include, and some tips for crafting an attention-grabbing resume.

What to Put on a Data Analyst Resume

The field of data analytics is rapidly expanding to meet the ever-growing amount of data being created. This means there are many job opportunities in this field for qualified individuals. However, this also means that the competition for these positions is increasing since hundreds of qualified candidates are applying to open Data Analyst positions. If you’re in the job market for employment in data analytics, you must make sure that your resume stands out from the competition. You will need to catch the hiring manager’s eye in the short time they study your resume. Because most recruiters spend less than seven seconds scanning a resume, you must make the most of this sliver of time by submitting a resume that is scannable and also showcases your work experience and why you are a good match for this specific position.

The following are six components of a strong data analytics resume to consider when crafting yours:

#1: Contact information and relevant professional profiles

It may seem straightforward, but your name and professional job title should be readily visible in a resume and likely be included in the header. This ensures that it will appear on all resume pages, even if they were to be separated. Other relevant contact information should also be included, such as your phone number and email address.

It’s also a good idea to include a link to your LinkedIn page. Because three-quarters of talent scouts turn to LinkedIn to find qualified candidates, you are much more likely to attract attention if your profile isn’t just available but is up-to-date. You can even include your LinkedIn profile in the header of your resume if you post work-related messages there. In addition, if you use other platforms such as Twitter to discuss your experience with data analytics, you may also link to them. However, if the social media handle contains any personal updates or posts, it’s best not to include it in your resume. You can also add links to Kaggle or GitHub profiles to the contact information section of a resume if you’d like to demonstrate your passion for working with data analytics as well as any past projects you’ve completed.

#2: Prior employment

Perhaps the most critical part of your data analytics resume is the section in which you list and describe past working experiences. In this section, which should be structured reverse chronologically with the most recent employment experience listed first, you will describe all employment you’ve had in a data-related field. It’s important to list the job title, employer, and length of employment and to note any important or relevant responsibilities and tasks you completed at this position. It’s also prudent to look at the job description for the position you will be sending your resume to see which skills they value, then highlight any skills you already developed at other positions.

#3: Projects or real-world experience with data

Depending on whether you are new to the field of data analytics or if you already have job experience working in this field, the contents of this section may change. For example, those who are new to applying for Data Analyst positions may not have job experience to include. Instead, this section provides a place to list any internship work or projects that you’ve completed that may be relevant to the position to which you’re applying, such as solo projects, open-source projects, or work done as part of a certificate or bootcamp.

#4 Education

Those who have recently graduated from college or graduate study in data analytics or a related field should list their educational information early on in their resume. However, if you graduated sometime in the past, the education section on your resume should follow work experience. In this section, include details such as the name of the school you attended, the degree you earned, your GPA (if it is relatively high), and any achievements or honors you earned while studying.

If you attended a certificate program instead of college, this information can be included in the education section. Make sure to mention any computer programming languages you learned, such as R or Python, as well as any relevant courses you completed that would apply to the job to which you’re applying.

#5: Skills

The “Skills” section of a data analytics resume is your chance to be specific and showcase any data analytic skills you currently possess, particularly those that the employer may be searching for in candidates. For example, if you’re applying to positions in the marketing industry, you may want to highlight any prior experience with visualizing data or performing data modeling.

# 6: Awards or Honors

Any recognition you’ve received for your work or studies should be listed here, especially those relevant to the job you’re applying for. Information such as the award's name, what it signifies, and when you received it are important details to include, with the most recent honors at the top of the list.

Data Analyst Resume Tips

The following are some tips to help you craft a solid and attention-grabbing data analytics resume:

Tip #1: Be concise

Space is limited when working with a resume, meaning each word must count. This speaks to the need to include only pertinent details and write about them succinctly without any unnecessary filler. In addition, to help audiences best engage with your data analytics resume, use active resume verbs when describing prior work experiences and keep all writing in the present tense.

Tip #2: Don’t clutter the resume

Because of how quickly most resumes are screened, it’s essential to use formatting techniques to optimize space and guide the eye. Consider implementing some of the following stylistic elements into your data analytics resume:

• Use consistent, easy-to-read headings and subheadings.
• Ensure you incorporate enough white space to help break up larger text portions and guide the eye from the top to the bottom of the resume.
• Use legible fonts that are an appropriate size, such as Times New Roman 12-point font. Use the same font throughout the resume.
• Save the resume as a PDF to ensure the formatting stays intact when the document is sent to various employers.

Tip #3: Consider adding an objective or resume summary

Depending on your circumstances, you may wish to add a resume summary or data analyst resume objective. For those who already work in data analytics or a related industry, a resume summary is a good idea to include. This functions similarly to an elevator pitch in that it is a short, snappy synopsis of any achievements, experiences, or skills you have in data analytics. An objective can be included in place of a summary if you are new to the field of data analytics and don’t have prior work experience in this industry or if you are in the process of changing careers. The objective functions similarly to a sales pitch and conveys to potential employers why you would be an asset to their organization.

Tip #4: Don’t omit relevant information

In some instances, adding additional information to your data analytics resume may be beneficial. For example, if you have any software licenses or publications, these details are impressive to hiring committees. You may also list any conferences you attended that focused on the skills listed in the job description.

In addition to ensuring that you’ve included all the relevant information on your resume, you also exclude anything that’s not directly relevant to the profession to which you are applying. Some examples of information you’ll want to leave out are most high school achievements (if you have a college degree) or work experience in unrelated fields, such as lifeguarding.

Data Analyst Resume Examples

The following three data analytics resumes are great examples of professional data analytics resumes in three different fields: marketing, data visualization, and business:

Example Resume #1: Marketing Analyst Resume

If you are interested in applying for Marketing Analyst positions, here is a sample resume and template for this field.

Example Resume #2: Tableau Developer Resume

Those who are interested in applying for Tableau Developer positions can look here to see a sample resume.

Example Resume #3: Business Analyst Resume

If you are seeking employment as a Business Analyst, here’s a sample resume and template to help structure yours.

Sign up for Hands-On Classes to Learn More About Data Analytics

Learning more about data analytics can open professional doors and lead to upward career mobility. If you’re interested in studying how to analyze and visualize data, Noble Desktop’s Python for Data Science Bootcamp is a great starting point. This intensive, 30-hour course covers core Python skills that are useful for the data sciences, such as an overview of the various data types and how to create data visualizations. Noble also offers an 18-hour SQL Bootcamp in which students learn how to filter data, write SQL queries, and gather insights from data.

For those looking to learn specifically about data analytics, courses such as the Data Analytics Certificate or Data Analytics Technologies Bootcamp are available in-person in NYC, as well as in the live online format. These rigorous learning options cover core data analysis tools like SQL, Excel, and Tableau.

If you’re looking for data analytics learning options close to home, you can also search for data analytic courses in-person or live online with the help of Noble’s Classes Near Me tool. Over 340 courses are currently available by Noble and other top educational providers in topics like data visualization and data analytics, among others.