I have been applying to so many roles and have not heard back! I have no idea what is wrong with my data analyst resume!
Does that sound like you? There’s a lot of advice out there on what makes a good resume; whether to make it pretty or not. However, no one has actual data on what really works.
JobStep is the first company that has actual data on what really works. In 2021, we applied to over 26,000 jobs on behalf of jobseekers. We know what needs to be in a resume in order to get interviews.
It sounds obvious but your resume needs to prove that you can do the work of a data analyst. Let’s recap what a data analyst does and share more information about the role, responsibilities, and what employers look for in a candidate.
A data analyst leverages company data to build comprehensive reports and presentations that answer difficult questions. They use tools like Excel, SQL, Tableau, PowerBI, Python, or R. Understanding these tools are typically core requirements for any data analyst role paying above $65K.
Your day-to-day job responsibilities as a data analyst will include:
Your resume will need to show a potential employer that you have experience analyzing data and using it to come to a conclusion. We will speak more to this throughout this guide. We also will include sample data analyst resumes at the end that you can use to model your resume after.
Here the questions recruiters ask themselves when they review your experiences on your resume. We recommend you take some time to write out these answers before you even write or update your resume.
After you answer the above questions, you can create resume bullet points that showcase your experience and skillsets.
Without the right education on your data analyst resume, you’ll almost certainly wind up in the rejection pile. Thankfully, the type of education you put on your resume doesn’t matter as much as showing how you’ve used the skills you’ve learned.
Broadly speaking, there are three ways that one could build the education required for a data analyst career. Traditional education, online courses, or learning on the job. Most data analysts combine 2 out of 3 as they progress through their careers.
Traditionally, the most popular data analyst degrees are economics, engineering, and business. Getting a bachelor’s degree in a technical field, such as statistics, science, mathematics, engineering, computer science or IT. Internships in college in data analysis, data mining, or advanced machine learning courses may help you land a role directly as a data scientist. Learn more about the differences between a data analyst and data scientist here (COMING SOON!).
There is also substantial demand for analytical individuals that many companies will hire those who got educated via online courses. At JobStep, we recommend data analytics and SQL online courses from programs like Mode Analytics SQL School, Khan Academy, and SQLZOO.
Finally, some data analysts learn on the job when they are in a different department, such as sales, marketing, customer success, and revenue operations. If you are in one of these departments, you can build in your own experiences by identifying value-add analyses for your employer. That way you can work on developing your analytical skill sets while aligning that with your employer’s goals and objectives.
Employers usually like to see experience working in team-settings in previous roles and experience analyzing data with SQL and excel. Your experience doesn’t have to be from paid work experiences. You can demonstrate having worked with SQL in side projects or from taking online courses.
With employers screening for specific skills and tools, it is important to have a Skills section at the bottom of your resume. We advise that you also sprinkle the skills you have and tools you have used in your resume bullet points. An example of a well-written Skills section is below:
It is more than okay if you do not have all the skills in the example above. What is well-done in the example is the use of keywords to bucket the tools used. A data analyst will need to have skills in data analysis, data visualization, business metric tracking, and database storage. Listing these out and including the tools in parentheses allows you to showcase your skill set.
Your ability to land a data analyst career should be determined by your data analysis skills, not your ability to write an optimized resume. With that, we would like to share what we call Mad Libs for Resume Bullets. You can start with the below bullet points and plug in details specific to your previous projects and experience.
Along with sharing some data analyst-specific advice, we also wanted to share some general best practices to keep in mind when creating a resume.
An effective resume bullet does three things efficiently:
Try your best to limit a large portion of resume bullets to 1 line. Too many multi-line resume bullets makes it hard for the employer and hiring manager to skim.
Other considerations to keep in mind when crafting your resume:
As a data analyst, you should talk about how you use SQL. If you want to one day move into data science, you should talk about how you’ve trained a model.
There are a few ways that you can format a resume bullet point:
Our team at JobStep specializes in helping job seekers break into and build data analyst careers. JobStep gets you 5 interviews in 6 weeks by finding and applying to jobs that are great for you.
Here’s how to optimize your resume to make sure you get the highest numbers of interviews.
Your data analyst resume will need to show a potential employer that you have experience analyzing data and using it to make a conclusion.
Emplowers usually like to see experience working in team-settings in previous roles and experience analyzing data with SQL and Excel.
Your experience doesn’t have to be from paid work experience. You can demonstrate having worked in SQL in side projects or from taking online courses.