Business Data Analyst Resume
Business Data Analyst Resume – Before starting to help data analysts find new jobs, one of the founders worked as a data analyst for six years. He’s reviewed hundreds of data analyst resumes and knows what it takes to land an interview.
Building your resume and your data analyst cover letter is the hardest part of this process, so we’ve selected nine great data analyst resume examples for different career levels to give you some inspiration.
Business Data Analyst Resume
Our nine data analyst resume samples, and our templates for 2022, Google Docs templates and free Word resume templates are work-proof and will help you put your best foot forward, so you always get the job you want!
Business Analyst Resume Examples & Writing Tips 2022 (free Guide)
According to the US Bureau of Labor Statistics, employment of computer and data scientists (including data analysts) is expected to grow by 16 percent from 2018 to 2028. This is much faster than average for other jobs!
It makes sense that people are flocking to apply for data analyst roles due to high demand and high salaries.
But that doesn’t mean you should give up. Applying for jobs online can feel like applying into a black hole, and we know it sucks. One of our founders took 77 job applications before landing his first data analyst job at Geico, and the next job was pretty easy to find.
One issue with applying for data analytics roles is that these titles are not standardized across companies. In one company, data analysts spend their time building reports in Tableau, while in another, they write machine learning models for production.
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Because of this variability, it can be difficult to be sure that you are including the right information in your data analysis. With this guide, you’ll put your best foot forward for whatever data analyst roles you’re looking for!
First you have to show that you have the right skills for the job! This means you need to accomplish two goals with your data analyst resume. First, you must be able to pass the automated keyword filters in the applicant tracking system (ATS) that companies use to screen applicants. Next, you’ll want to demonstrate your technical skills to the person reviewing your resume.
If you’re not sure which skills to include, we’ve researched the data to find out which skills are most in demand for companies hiring data analysts.
These two goals, unfortunately, are often at odds with each other. If your goal is just to get past the ATS, you’ll list each skill to get your foot in the door:
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The problem? This method is a huge red flag for technical hiring managers. You should only include skills that you are comfortable discussing in your data analyst interview. Additionally, your skills section should not take up more than 20 percent of the page.
Any reasonable employer would not expect you to know SAS, R and Python. Instead, just list the technical skills you’ve coded in the past. And avoid including skills like “data mining” or “data analysis” because a technical hiring manager knows these are meaningless words. Instead of “data mining,” list the actual techniques you used, such as “decision trees” or “logistic regression.”
But even when narrowing it down, sometimes your skills list looks cluttered and hard to read. Never fear; There are many ways to organize your skills room! For starters, you can list how proficient you are at your skills (“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 device.
For programming languages, specify the libraries and frameworks used by that programming language for data visualization and manipulation.
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Often, you don’t need to include a resume objective or resume summary, which many data analysts do. If a resume summary or objective doesn’t add value to your application, it’s okay to leave it out.
Why leave this out? It is repetitive. Let’s say you’ve already demonstrated in your report that you’ve used tools like Python and SQL to turn data into actionable insights. In that case, your objective won’t tell anyone looking at your resume any new information.
Resumes are similar, but for candidates with more than 10 years of experience and may include more personal accomplishments. There isn’t much difference between a resume summary or objective; You just need to know when to include them.
When a hiring manager has 50+ resumes for a given role, they quickly look for reasons to say “no.” By using these formatting tips, you’ll make it easier for the hiring manager to see your value and ask you for an interview.
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Of all the places to make mistakes, your contact information is the worst place to make a typo. One of our team members recounted his first days out of college as a data analyst. When applying for a job, they accidentally wrote the wrong email address on their resumes for seven different positions.
Even if they were perfectly qualified for the role, there was no way to get them because of a small mistake. So trust us when we say that you should triple check this section for any spelling, grammar or link errors.
As part of your contact information, you should include your name and the role you’re applying for (even if it’s not your current role).
You do not need to include your full address in this section, but you should list your city and zip code. If your employer chooses that method, you’ll need your phone number.
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Finally, include a link to your LinkedIn profile and anything else that explains why you’re a great data analyst. If you have an active Github, include a link to it. If you’ve done a lot of Kaggle competitions, include a link to your profile. Do you have a personal blog where you talk about election data? Be sure to include a link.
If you are an entry-level data analyst looking for your first full-time role, including projects is a must. However, the more work experience you have, the more critical the projects should be. Unless you have more than four years of experience in the field, you should only include a project that you are particularly proud of.
Which projects should you include? Anything where you identify (or are given) a problem and use data to come up with an answer to that problem. It’s okay if it’s a class project, but even better if you take the initiative yourself.
If you don’t have such projects, now is the time to work on some. Have a question you can’t answer? That experiment you’ve been dying to try? Think of ways to collect and analyze data to satisfy your curiosity.
Data Analyst Resume Examples & Writing Tips 2022 (free Guide)
Here’s an example: One of our co-founders had the idea that the major job boards (of course, Glassdoor and LinkedIn) had essentially the same jobs for data science roles. Therefore, he collected data manually, analyzed it and wrote about it to decide the best job boards for data scientists.
The projects you include don’t need to be groundbreaking or ground-breaking. Employers just want to see that you can ask a question, use information to answer the question, and present your findings in a logical and clear manner.
Your Projects section is an opportunity to provide additional context around the programming languages and libraries you listed in your “Skills” section.
As with the “Projects” section, your education section for entry-level data analysts will be longer than for experienced data analysts. For entry-level data analysts, you’ll want to include relevant courses you’ve taken in school related to data analytics.
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Courses related to data analysis include mathematics, statistics, programming, and economics. To be an effective data analyst, you must apply the principles you learn in these classes to real-world problems and data sets.
Regardless of your experience level, you should always mention the school you attended, where you studied (including minors or certificates), and when you graduated. This will be the place to list any bootcamps or related online courses you’ve taken in the field.
If your background is in academia, you can list any publications you have co-authored. Be sure to include the title of the magazine and a link that allows the hiring manager to read more if they are interested.
Only list your GPA if it’s something you want to highlight – generally only list your GPA if you’re an entry-level student and got something above a 3.0.
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You analyze data for a living, so you know that numbers count when it comes to data. So when talking about your work experience, your goal should be to highlight your accomplishments using numbers and estimates.
“Performed customer segmentation analysis using SQL and Excel and recommended an email campaign for a customer segment.”
When discussing your work, especially if it’s a group project, emphasize your unique contributions. For example, you may have made a product recommendation based on previous analysis. you need
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