Build a professional data analyst resume in minutes. Browse through our resume examples to identify the best way to word your resume. Then choose from 12+ resume templates to create your data analyst resume.
Zippia allows you to choose from different easy-to-use Data Analyst templates, and provides you with expert advice. Using the templates, you can rest assured that the structure and format of your Data Analyst resume is top notch. Choose a template with the colors, fonts & text sizes that are appropriate for your industry.
Your name should be the biggest text on the page and be at or near the top of the document.
Your address doesn't need to include your street name or house number - listing your city and state works just fine.
Your email address should be professional, but not your current work email address. It's not a good look to use your work email for personal projects (job-searching).
Your social media can be included if you have a fully-fledged LinkedIn page or another social media page that showcases your relevant skill set.
Your resume's education section should include:
Optional subsections for your education section include:
Other tips to consider when writing your education section include:
The most important part of any resume is the experience section. Recruiters and hiring managers expect to see your experience listed in reverse chronological order, meaning that you should begin with your most recent experience and then work backwards.
Don't just list your job duties below each job entry. Instead, make sure most of your bullet points discuss impressive achievements from your past positions. Whenever you can, use numbers to contextualize your accomplishments for the hiring manager reading your resume.
It's okay if you can't include exact percentages or dollar figures. There's a big difference even between saying "Managed a team of engineers" and "Managed a team of 6 engineers over a 9-month project."
Most importantly, make sure that the experience you include is relevant to the job you're applying for. Use the job description to ensure that each bullet point on your resume is appropriate and helpful.
Pavel Chernyavskiy Ph.D.
Assistant Professor of Statistics, University of Wyoming
Good software skills (R, Python, C++, etc.) are pretty standard at this point, so applicants should aim to differentiate themselves in other ways. I like to see applicants demonstrate evidence they have been involved in a project: for undergraduates; this might be a poster presentation or a capstone project; for graduate students, this might be co-authorship on a published manuscript thesis work.
I value teaching experience since it usually implies that the applicant is a good communicator who can figure out how to manage a classroom and work with a range of stakeholders.Show more
Certifications can be a powerful tool to show employers that you know your stuff. If you have any of these certifications, make sure to put them on your Data Analyst resume:
A resume summary statement is a 1-3 sentence spiel at the top of your resume that quickly summarizes who you are and what you have to offer. In this section, include your job title, years of experience (if it's 3+), and an impressive accomplishment, if you have space for it.
Remember to address skills and experiences that are emphasized in the job description.
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Examples of data analysis skills include analytical thinking, problem-solving, technical expertise, data analysis, communication, and teamwork.
A good data analyst should have skills that guide them in manipulating and analyzing large datasets, gaining new information and insights, and then communicating this information effectively to stakeholders and management.
Being able to find new information in data is not as simple as it may sound. To do this requires an understanding of certain coding languages, statistics, databases, and lots of critical thinking.
Data analysts must develop skills to help them gather, organize, and interpret data (e.g., sales figures, inventories, operating costs) and look for patterns or trends. They also need skills related to helping others understand what to do with this information in the form of suggestions that can guide strategic business planning and decisions.
Top skills every data analyst should have:
Data Mining
Data Visualization
Data Cleaning
Structured Query Language (SQL)
Microsoft Excel
Critical Thinking
R or Python-Statistical Programming (Pandas)
Machine Learning
Communication
Project management
Research