Data Analyst Resume Sample
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Why this resume works
- Because mid-level roles exist in a non-junior, non-senior-type limbo, it's crucial to identify and exemplify every bit of experience possible for your data analyst resume. If you have a target company or niche in mind, pay special attention to the individual data analyst job description, looking for keywords, the mission statement, and even the company culture.
- Once you know what the employers are looking for, you can include directly applicable keywords and matching language in your work experience bullet points (provided the keywords truly describe you!)
- After you've determined the content and matching keywords for your bullet points, add in any quantifiable metrics that can showcase your experience and help prove your merit.
SQL Data Analyst Resume Sample
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Why this resume works
- Your SQL data analyst resume needs to be powerful regardless of you how much experience you have. Even if you only have internships, choose your work experience bullet points wisely since customizing your resume is the best way to catch an employer's attention (and pass the ATS scan).
- Start by analyzing the requirements in data analyst job descriptions to get an idea of what employers require.
- Speaking of customization, commonly interchangeable titles such as "data analyst," "data developer," and "data engineer" have virtually identical responsibilities. Despite their similarities, recruiters will respond best if your previous titles match the job for which you've applied.
- Speak with your current manager if you're anxious about changing position titles. Always err on the side of caution, and ask for permission instead of forgiveness.
Entry-Level Data Analyst Resume Sample
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Why this resume works
- Unsure how to start a resume? No problem! Start by using a solid resume outline to help you get a feel for what a resume looks like, then add your experience and skills one at a time.
- As an aspiring professional, you have some options for showcasing your available skillset on your entry-level data analyst resume.
- The first option is to demonstrate programming, testing, modeling, and data visualization competency by building well-designed projects that solve real problems through code.
- The key here isn't reinventing the wheel but creating something dynamic and unique that can't be easily replicated with a few Google searches and a video tutorial.
- The second option is to invest time and effort into internships. Internships are a fantastic way for an aspiring degree-holder to gain on-the-job experience.
- Some internships require a fully completed degree before starting. Although this is becoming more uncommon with the introduction of online coding trade schools (boot camps), do some research regarding individual markets and locations.
Senior Data Analyst Resume Sample
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Why this resume works
- As a senior data analyst, the need for a comprehensive career objective dwindles. Your senior data analyst resume should heavily focus on work history, excellent KPIs, and leadership.
- Highlight a lengthy career in data analyst roles with quantifiable data from multiple sources, jobs, leadership, and mentoring.
- With experience comes a whole host of skills; however, don't list every ability you have in your resume skills section.
- Only include highly relevant ones like Python, SQL, Tableau, and Excel with additional modeling, data visualization, and product analytics keywords.
Data Analytics Manager Resume Sample
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- Double, triple, and quadruple-check your grammar and spelling. One error can send your resume into the "no" pile!
- Each bullet point on your resume should be a self-contained, complete thought.
When a hiring manager reviews 50+ resumes for a given role, they quickly look for reasons to say "no." By using these resume-formatting tips, you make it easier for the hiring manager to see your worth and ask you for an interview, getting you one step closer to a job.
Of all the places to make an error, your contact information is the worst place to have it happen. One of our team members recounted their early days out of college as a data analyst. When they were applying for jobs, they accidentally wrote the wrong email address on their resume for seven different positions.
Even if they were perfectly qualified for the role, there was no way to contact them because of a minor mistake. So believe us when we say you need to 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 don't need to include your full address in this section, but you should list your city and zip code. You also need your phone number just in case your employer prefers that method.
Finally, include a link to your LinkedIn profile and anything else that might convey why you're a great data analyst. If you have an active Github, include a link to that. If you do a lot of Kaggle contests, include a link to your profile. Have a personal blog where you talk about election data? Be sure to include a link.
Data analyst projects for your resume
If you're entry-level and looking for your first full-time role, including projects on your data analyst resume is an absolute must. However, the more work experience you get, the more projects should become less critical. By the time you have four-plus years of experience in the field, you should only include a project of which you're exceptionally proud.
What projects should you list? Anything where you identified (or were given) a problem and you used data to come up with an answer to that problem. It's okay if it's a class project, but it's even better if you took the initiative yourself.
If you don't have any such projects, now is the time to work on some. Do you have a question you've never answered? An experiment you've been longing to try? Think of a way to gather and analyze data to sate your curiosity.
Here's an example: one of our founders had a hunch that the major job boards (Indeed, Glassdoor, and LinkedIn) essentially had the same jobs for data science roles. So, he manually collected data, analyzed it, and wrote about it to determine the best job board for data scientists.
The projects you include don't need to be exhaustive or ground-breaking. Employers just want to see that you can ask a question, use data to answer it, and present your findings reasonably and clearly.
Good—show you can answer your own questions with data
When talking about your projects, here's how you should frame what you did:
- Clearly state the question you were answering or the problem you were trying to solve
- Show what tools or languages you used to solve the problem
- State the impact of the work you did
Your projects section is also an opportunity to provide more context around the programming languages and libraries you listed in your "skills" section.
Like the "projects" section, the education section of your resume will be longer for entry-level data analysts relative to more experienced data analysts. You'll want to include relevant courses you took in school related to data analytics for entry-level data analysts.
Courses relevant to data analytics are any mathematics, statistics, programming, and economics classes you took. To be an effective data analyst, you need to apply the principles you learned in these classes to real-world problems and datasets.
For entry-level roles, include relevant classes you took in school
Regardless of your experience level, you should always mention the school you attended, what you majored in (including minors or certifications), and when you graduated. This would also be the place to list any boot camps or relevant online courses you may have taken in the field.
If your background is in academia, you can also list any publications you may have co-authored. Be sure to include the title of the magazine and a link to allow the hiring manager to read further if they're interested.
Only mention your GPA on your resume if it's something you want to highlight—generally, only list your GPA if you're entry-level and obtained anything above a 3.0.
You analyze data for a living, so you know that numbers count when it comes to information. So when you're talking about your work experience, your goal should be to highlight your accomplishments using numbers and estimates.
The formula for talking about work experience
"Specific contribution to project mentioning specific tools and skills"
"quantitative impact of the project"
"Performed a customer cohort analysis using SQL and Excel and recommended an email campaign for one customer segment"
"that lifted monthly retention by 10%"
When discussing your work, especially if it was a team project, emphasize your specific contributions. For example, you may have made a product recommendation based on a previous analysis. You'd want to talk about that particular recommendation on your resume instead of the built feature.
When talking about the quantitative impact, it's okay to talk about the project as a whole. Following the example above, it'd be impossible to tease out the value of your product recommendation versus the engineer's impact who built the feature since it's a team effort. You'd say the feature had a revenue impact of $X on your resume.
Data analysts work across many different teams and projects in a company, so it's not always easy to tie your work to a revenue impact. Still, try estimating your contributions using metrics to make your resume stand out.
These can be very rough estimates; you just want to make it clear that you've contributed to positive outcomes for the businesses where you worked.
Ways to quantify the impact of your analytics work
- Improved customer conversion rate
- "Used Python and SQL to determine a specific change in the landing page, resulting in a 10% boost in free trial activation rate"
- Saved manual reporting time
- "Streamlined and automated a key business report in Tableau, saving the team 10 hours of reporting each week"
- Reduced costs
- "Used SQL and Excel to recommend ending contracts with worst-performing vendors, resulting in a costs savings of $100,000 annually"
- Built data visualizations to help executives
- "Built data visualizations in Excel to demonstrate the efficacy of marketing plan, resulting in the close of a $1.3M Series A"
- Improved customer retention
- "Determined through analysis in Python that emailing customers who had been inactive for 7 days resulted in a retention improvement of 7 basis points"
- Improved business-specific KPI like time-to-hire
- "Identified procedural areas of improvement in hiring data to improve the time-to-hire for key roles by 11 days"
- Improved customer satisfaction
- "Used SQL and Excel to identify common complaints amongst new customers, leading to changes that improved new customer satisfaction by 14%"
When formatting your work experience, always list your most recent work at the top of your resume and list your other positions in reverse-chronological order.
Just to hammer home our point even further, here's an example of the same work experience. One is stated in a quantitative impact, and one is not.
X Bad—no quantitative impact
Tailor your resume for each job
For each role to which you apply, make minor edits to your resume based on the data analyst job description. Fortunately, youdon't have to completely rewrite your resume; just a few tweaks will do.
For example, let's say you've done projects in both Python and R, and your resume heavily leans into your Python experience. If you apply to a job that mentions R, you should change your resume to discuss your R experience.
Similarly, if you have specific projects that relate to the job you're applying for, include those projects. If you're applying for a marketing data analyst role and have experience building marketing mix models, your application will become significantly stronger by mentioning those mix models.
Let's say you're applying to this job:
This seems like a heavy data visualization role. Instead of mentioning predictive modeling, talk extensively about your experience building robust data visualization in Tableau.
How to Write an Effective Data Analyst Resume
Here are the major takeaways you should keep in mind when writing a professional resume:
- Keep it to one page and proofread, proofread, proofread.
- For an entry-level role, mention any math/stats/econ/programming classes you took in college.
- Otherwise, don't let your education section take up a lot of space.
- You don't need a summary or objective section on your resume unless you're undergoing a career change or have over 10 years of experience.
- Only include skills on your resume for which you'd be comfortable being interviewed.
- Mention your specific contributions and quantify the overall project's impact on the business.
By following this guide, you'll be able to quickly and convincingly make the case that you're a great fit for the data analyst role for which you're applying.
Applying for jobs isn't easy, but you've taken a huge first step toward landing that dream job. Now all that's left is to write, double-check your resume for errors, and submit it to your dream job!