Data Analyst Resume Entry Level – The number of data analysts is expected to grow by 25 percent between 2020 and 2030, plus increased salary transparency laws make this an ideal time to land a job as a data analyst.
Fun fact: before we started, one of our co-founders worked as a data analyst for six years. With his guidance, we’ve reviewed many data analyst resumes to find out what helps data analysts get more interviews.
Data Analyst Resume Entry Level
Building your data analyst resume and cover letter is the hardest part of the process. To inspire you, we have selected the 20 best data analyst resume samples for different career stages.
Junior Data Analyst Resume Sample
Our data analyst resume examples are proven to help you put your best foot forward to land the job you’ve always wanted in 2023.
According to A.S. Bureau of Labor Statistics employment of data and information scientists (including data analysts) is expected to grow 16 percent from 2018 to 2028. This is much faster than the average for other jobs!
Due to the high demand and high salaries, it makes sense that people would flock to apply for data analyst jobs.
But that doesn’t mean you should be discouraged. Looking for a job online can feel like searching a black hole, and we know it sucks. It took our co-founder 77 job applications before he landed his first data analyst job at Geico, and subsequent jobs were much easier to find.
Professional Reporting Analyst Resume Example
One problem with applying for a data analytics role is that this title is not standardized across companies. At one company, data analysts may spend their time creating reports in Tableau, while at another they write machine learning models for production.
Because of this variability, it can be difficult to ensure that you include accurate information in your data analytics resume. With this guide, you will give your best no matter what data analyst role you are applying for!
First you have to show that you have the right skills for the job! This means you should achieve two goals with the skills section of your data analyst resume. First, you need to be able to bypass the automatic keyword filter in the applicant tracking system (ATS), which is what employers use to screen applicants. Next, you want to demonstrate your technical prowess to the person reviewing your resume.
If you’re not sure which skills to include, we analyze the data to find out which skills are most in demand by companies hiring data analysts.
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Unfortunately, these two goals are largely at odds with each other. If your goal is simply to pass the ATS, you would list all the skills for a shot:
Problem? This method is a big wake-up call for technical hiring managers. You should only include skills that you feel comfortable discussing in your data analyst interview. Also, your skills section should not take up more than 20 percent of the page.
Python. Instead, you simply list the technical skills you’ve previously coded. And avoid including skills like “data mining” or “data analysis” because technical hiring managers know these are just general terms that don’t mean much. Instead of “data mining”, list the actual techniques you’ve used, such as “decision trees” or “logistic regression”.
But even when you narrow it down, your list of skills sometimes looks cluttered and hard to read. Never fear; There are many ways to organize your skill sections! For starters, you can list your skills based on how proficient you are with them (“Advanced” vs. “Familiar”, for example). Alternatively, you can list your skills by skill type. You can even mention the years of experience you have with each tool.
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For a programming language, specify the libraries and frameworks you use for data visualization and manipulation in that programming language.
Most of the time, you don’t need to include a resume objective or resume summary; a mistake many data analysts make. If the CV summary or objective does not add value to your application, it is okay to leave it.
Why leave this? That is too much. Let’s say you’ve listed on your resume that you use tools like Python and SQL to turn data into actionable insights. In this case, your goal is not to tell the person reviewing your resume any new information.
A similar summary, but for candidates with more than 10 years of experience and may include more personal achievements. There isn’t much difference between a resume summary or objective; all you need to know is when to enter it.
Data Analyst Cv Example + Writing Guide [get Hired Quickly]
When hiring managers review more than 50 resumes for a given role, they are quick to find reasons to say “no.” By using these resume formatting tips, you’ll make it easier for hiring managers to see your value and ask you for an interview, bringing you one step closer to the job.
Place to make it happen. One of our team members talked about his early college days as a data analyst. When applying for a job, they accidentally put the wrong email address on their CV for seven different positions.
Although they were qualified for the role, there was no way to contact them because of a small mistake. So trust us when we say you need to triple check this section for spelling, grammar or link errors.
As part of your contact details, you must include your name and the role you are applying for (even if it is not your current role).
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You do not need to enter your full address in this section, but you must include your city and zip code. You will also need your phone number if your employer prefers that method.
Finally, include a link to your LinkedIn profile and anything else that can demonstrate why you’re such a great data analyst. If you have an active Github, include a link to it. If you do a lot of Kaggle competitions, include a link to your profile. Do you have a personal blog where you talk about electoral data? Be sure to include a link.
If you’re a beginner looking for your first full-time role, including a project on your data analyst resume is a must. But the more work experience you get, the less critical projects will be. When you have more than four years of experience in the field, you should only go into projects you are very proud of.
Which projects should you register? Anything where you identify (or are presented with) a problem and you use data to come up with an answer to that problem. It’s great if it’s a class project, but even better if you take the initiative yourself.
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If you don’t have such a project, now is the time to tackle some. Have a question you haven’t answered yet? An experiment you’ve been meaning to try? Think of ways to collect and analyze data to satisfy your curiosity.
Here’s an example: one of our founders had an inkling that the major job boards (Indeed, Glassdoor, and LinkedIn) had essentially the same jobs for data science roles. So he collects data manually, analyzes it and rewrites it to determine the best job boards for data scientists.
The projects you include do not have to be complete or innovative. Employers just want to see that you can ask questions, use data to answer them, and present your results fairly and clearly.
This part of your project is also an opportunity to provide more context around the programming languages and libraries you listed in the “skills” section.
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Like the “projects” section, the education portion of your resume will be longer for entry-level data analysts than for more experienced data analysts. You’ll want to include a relevant course you took in school related to data analysis for entry-level data analysts.
Courses relevant to data analysis are the math, statistics, programming, and economics courses you took. To become an effective data analyst, you must apply the principles you learn in this class to real-world problems and data sets.
Regardless of your experience level, you should always mention what school you attended, what your major was (including minors or certifications), and when you graduated. This will also be the place to list relevant boot camps or online courses you may have taken in the field.
If your background is academic, you can also list any publications that you can co-author. Be sure to include the magazine title and a link so the hiring manager can read more if they are interested.
Data Entry Analyst Resume Sample
Only mention your GPA on your resume if it’s something you want to highlight – in general, you should only list your GPA if you were entry-level and earned anything above a 3.0.
You analyze data for a living, so you know that numbers matter when it comes to information. So when talking about your work experience, your aim should be to highlight your achievements using numbers and estimates.
“Perform customer group analysis using SQL and Excel and recommend email campaigns for a customer segment”
When discussing your work, especially if it’s a team project, emphasize your specific contributions. For example, you may have made product recommendations based on previous analysis. You want to talk about the specific recommendation on your resume instead of a created function.
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When talking about quantitative effects, it is okay to talk about the project as a whole. Following the example above, no way
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