How to Write a Data Analyst Resume and Land Your Dream Job

Key Points

• Learn about the different elements of your data analyst resume
• Discover the major points you want to highlight on your resume
• See how you can create an outstanding resume that will help you secure your dream job

A data analyst has the training and technical skills to work closely with data sets, parse apart what they mean with statistical analysis, and know-how to apply what they learn for problem-solving. In addition, their data analyst skills help them uncover patterns and trends in the data to apply this information to provide business intelligence and further advance the organization.

Data professionals can work in a variety of industries, from sales to health care. As businesses realize the power of using Big Data to guide their decisions, improve their methodologies, and better serve their customers, data analysts will find they are in high demand.

Those interested in entering this field will want to make sure they put their best foot forward with a resume that will catch the attention of the hiring team. We’ll explore what you need to know about writing a data analyst resume so that you can move forward confidently with your job search.

At the top of your resume, include your contact information. Featuring your contact details at the top will ensure the hiring manager will know how to contact you.

Your contact information should not contain any information from your current job, though. In other words, don’t list your employment location, work phone number, or work email. At the same time, make sure that you use a professional email address.

To create an effective data analyst resume summary, highlight your accomplishments in a clear, easy-to-understand format. Keep the summary to a few action-packed sentences that the hiring manager can read quickly.

Focus on the following elements:

• Let the new company know what you can do for them if hired.
• Draw attention to specific things you have accomplished. For example, “identified gaps in sales processes and increased efficiency by 20%” sounds more appealing than “used data analytics to study the effectiveness of sales processes.”
• Highlight any important skills or traits you have. For example, you can incorporate any programming languages you know and your experience with data modeling or data warehousing. Don’t forget soft skills, as well. If you excel as a problem-solver, for example, or have excellent presentation skills, you can mention these, too.

On your resume, highlight your relevant work experience. Depending on your work history, you might have many jobs to sort through when determining what to include. Focus on jobs that fit the following situations:

• The positions were highly relevant to the job you want now. However, if you are switching industries, focus on the jobs that have overlap in other areas. For example, consider if you have managerial skills or other types of analysis.
• If you have worked in the industry for a while, highlight similar responsibilities and tasks. This demonstrates how they have prepared you for the prospective job.

As you list your work experience, try to incorporate keywords from the job description to show how these jobs have helped you develop similar skills to those that the hiring manager wants to see in candidates. Talk about how you incorporated data analysis and understanding into your previous jobs, how you used that data to benefit the business and specific achievements. Use metrics, when possible, to emphasize what you accomplished.

In the field of data analysis, you might find that your education comes from a variety of places. Many people earn degrees in data science or computer science. Others may have received their bachelor’s degree in an unrelated field and transitioned to data analysis later in their career. There are various certificates, associate degrees, and master’s degrees that you could have used to bridge your education gap as you prepared for the career switch. Your credentials and education section should, therefore, list achievements, including:

• Any advanced degrees pertinent to data science
• Any certificates you have pursued in the subject area
• Any training opportunities you have taken advantage of, such as an online course to learn a new programming language

Showcasing your resume is your opportunity to let your skills and education shine so that the potential employer can see what you have learned and achieved. Some applicants might find it helpful to use bullet points for their educational history, like a bullet for a bachelor’s degree, a second for a master’s degree, and then a third for a certificate or similar educational achievement.

As you spell out your education and skills, you also want to highlight abilities that employers want to see in data scientists. To know the areas that will matter the most to this particular employer, you can review the job description, as the employer will highlight specific requirements.

Regardless, there are a few types of skills that hiring teams typically want to see from their hires in the field of data science. Some areas to consider as you list your qualifications include:

• Experience with different programming languages, including SQL, Java, and Python
• Your years of experience and understanding in data collection, data mining, data visualization, data management, predictive analysis, and analyzing data sets to make decisions
• Presentation skills and experience taking complicated data topics and making them understandable for others in the company
• Experience with SPSS
• Skills in machine learning
• Experience with common spreadsheet programs, including Microsoft Excel
• Close attention to detail
• Problem-solving skills
• A high level of mathematical ability

Once you have created your initial resume, please review it carefully and thoroughly. Typos or confusing layouts can easily create challenges for those reading the resume, resulting in you getting passed over for the job you want. To give your data analyst resume the best editing job possible, start by reading over the job description again and gauging how well you reflected what the employer wants to see. Next, proofread your resume carefully, checking for errors, typos, or ways to make your sentences clearer and engaging.

Once you have given your resume a careful read-through, reach out to a friend or family member to read it for you, particularly one who will give you honest feedback. Ask them to help you check for typos or errors and give you feedback about its clarity, layout, and ease of finding relevant information.

Give it one last careful read yourself, trying your hardest to view the resume through the eyes of a hiring manager or recruiter.

Once you’ve created your data analyst resume, you have two final steps. The first is to make sure your LinkedIn profile is up to date. Hiring managers will often look at LinkedIn profiles to learn more about candidates, including browsing their skills section, education history, and how they present online.

Secondly, you will need to write your cover letter. Whether you want to become a senior data analyst or find an entry-level data analyst job, you need a cover letter explaining what makes you the right candidate.

Once you’ve gotten through these steps, you’re ready to submit your job application for the data analysis job.

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