Data Analyst Resume Sample
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
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
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
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
- 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!
The reverse-chronological work history format is the most common and is especially ideal for anyone who's on a traditional career trajectory. It lists your work history in reverse chronological order, starting with your current engagement and ending with your first job.
Are Data Analysts in demand 2022? ›
In 2022, more than half of all businesses around the globe view data analytics as a core component of their operations. With the ever-increasing amount of data being created, the need for qualified Data Analysts to analyze it is at an all-time high and will likely continue to increase in the coming years.
What are the best resume templates in 2022? ›
Our researchers have interviewed over fifty employers from diverse fields to discover that the reverse-chronological, functional, and combination resume formats are the best suited for the year 2022. These three resume formats are unique in their own ways.
What skills should I list on my resume for data analyst? ›
How far back should a 2022 resume go? ›
Top Data Analyst Resume Skills
- Microsoft Excel.
- Statistical programming languages.
- A/B testing.
- Web analytics.
- Project management.
Your resume should go back 10–15 years assuming it's all relevant experience. However, it all depends on your work history: how much experience you have, whether you have gaps in employment or scored freelance gigs. As long as your resume is targeted to the job ad, it can be even 2-3 pages.
What are employers looking for in a resume 2022? ›
There are mainly four things that recruiters and hiring managers look for in the resume scanning stage: work experience, education, skill set, and personality.
Do data analysts get paid well? ›
Data analysts are typically paid well for their skills. In this article, you'll learn how much data analysts earn on average, as well as how various factors, like experience, industry, location, and job title can impact your data analyst salary.
Is data analyst stressful? ›
Several data professionals have defined data analytics as a stressful career. So, if you are someone planning on taking up data analytics and science as a career, it is high time that you rethink and make an informed decision.
What makes a good data analyst? ›
Ability to demonstrate the data proficiency, flair and mastery on data manipulation to solve or answer organisations questions should be a habit of a good analyst. This quality would help the analyst develop the ability to spot when things or data issue are very wrong.
What are the top three 3 most popular types of resumes? ›
There are three common resume formats: chronological, functional, and combination.
What 3 skills are involved in data analyst? ›
This is the most common type of resume format and is generally preferred by most hiring managers. A chronological resume leads with your work history, which should list your current and previous positions in reverse chronological order.
What are three attributes of a data analyst? ›
Below, we've listed the top 11 technical and soft skills required to become a data analyst:
- Data Visualization.
- Data Cleaning.
- SQL and NoSQL.
- Machine Learning.
- Linear Algebra and Calculus.
What are three best qualities that great data analysts have in common? ›
To become a Data Analyst, you will need to:
- be good with numbers.
- have great IT skills, including being familiar with databases and query languages.
- have good analytical skills.
- be good at solving problems.
- to be able to work to deadlines.
- pay attention to details and accuracy.
- be able to work as part of a team.
What is the 30 second rule for resume? ›
7 traits of a good data analyst
- Trait 1 – Natural curiosity.
- Trait 2 – Critical thinking.
- Trait 3 – Understanding your data.
- Trait 4 – High attention to detail.
- Trait 5 – Mastering technologies and tools.
- Trait 6 – Ability to explain your results in simple terms.
- Trait 7 – Continuous learning.
In a competitive labor market, your resume must get you on the interview pile in 30 seconds or less. Otherwise, you will end up in the reject pile and never get a chance to sell yourself in person. The best format and structure for resumes is a never-ending debate.
What should you not put on a resume for 2022? ›
Is it ok to have a 2 page resume 2022? ›
12 Things to Leave Off Your Resume
- High School Information. ...
- References. ...
- Personal Information. ...
- Your Age. ...
- Your Exact Street Address. ...
- A Career Objective. ...
- Your Current Work Contacts. ...
- Your Personal Email Address.
It is important to keep the information you provide short, simple, and to-the-point. For many applicants though, that can't be achieved in a single page, and it's appropriate to write a two-page resume.
What are the 3 things your resume will tell an employer? ›
Resumes tell the employer about your experiences, skills and work history. Use your resume to highlight items that indicate you are a good worker, are qualified for the position and bring desirable skills to the job.
What are employers not looking for in a resume? ›
What are 5 things that should be included on a resume? ›
What you should never put on your resume
- A career objective. Put simply: A career objective is largely obsolete. ...
- Your home address. ...
- Soft skills in a skills section. ...
- References. ...
- Stylized fonts. ...
- High school education. ...
- Your photograph. ...
- Company-specific jargon.
Commonly suggested parts are your contact information, resume profile or summary, experience, education and skills. Your resume may also stand out from the rest if you include optional sections describing your hobbies or accomplishments.
Candidates with advanced skills or at least three years of work experience on their resume can earn an average salary of over $100,000 per year.
Do data analysts do a lot of coding? ›
Do Data Analysts Code? Some Data Analysts do have to code as part of their day-to-day work, but coding skills are not typically required for jobs in data analysis.
Which analyst has highest salary? ›
The top 5 highest paying jobs as Data Analyst with reported salaries are: analyst - ₹27lakhs per year. lead consultant - ₹24lakhs per year. data analyst - ₹19lakhs per year.
What does an entry-level data analyst do? ›
What Does an Entry-Level Data Analyst Do? The job duties of an entry-level data analyst include working to collect, manage, and analyze data. In this career, your responsibilities often revolve around performing research on business or industry data to define trends or assess performance in a particular sector.
What does a data analyst do on a daily basis? ›
A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They work in many industries, including business, finance, criminal justice, science, medicine, and government.
Do data analysts work long hours? ›
Does a data analyst work many hours in a week? As a data analyst, you should expect to work regular business hours in a week. Typically, this can be from 40 to 60 hours per week.
What is your greatest strength data analyst? ›
“I think the two biggest traits that are important for successful data analysts to have are extensive technical knowledge and strong communication skills. Technical knowledge is needed to complete the majority of a data analyst's responsibilities.
What soft skills do data analysts need? ›
Hard or technical skills are very important to become a successful data analytics professional. But to truly deliver maximum business value, data analytics professionals need to complement hard skills with strong soft skills, especially communication, collaboration, critical thinking, curiosity and creativity.
What are two important first steps in data analysis? ›
The first step is to collect the data through primary or secondary research. The next step is to make an inference about the collected data. The third step in this case will involve SWOT Analysis. SWOT Analysis stands for Strength, Weakness, Opportunity and Threat of the data under study.
What is a good personal summary? ›
Two to ﬁve phrases written in a bulleted form or brief paragraph will do. Think of the summary as a snapshot of your skills, accomplishments, and knowledge. Label your proﬁle professionally: Summary of Qualiﬁcations, Career Proﬁle, Career Highlights, Professional Summary, or just Summary or Proﬁle.
Example: "I am ambitious and driven. I thrive on challenges and constantly set goals for myself, so I have something to strive toward. I'm not comfortable with settling, and I'm always looking for an opportunity to do better and achieve greatness. I was promoted three times in less than two years in my previous role."
How do I promote myself on my resume? ›
Which are red flags on a resume? ›
How to sell yourself on a resume
- Use professional contact information. The first step toward standing out when submitting a resume for a job application is to ensure you're providing employers with accurate and professional contact information. ...
- Narrow down your credentials. ...
- Keep it brief. ...
- Emphasize your strengths. ...
- Be honest.
What are some things you should avoid when writing a resume? ›
10 resume red flags to look out for when you're hiring
- Spelling, grammar, and punctuation issues. ...
- Poor formatting. ...
- Failure to follow directions. ...
- Lack of customization. ...
- Unexplained employment gaps. ...
- Regression or lack of progression. ...
- Multiple career changes. ...
- Unprofessional social media presence.
What information should be left off of a resume? ›
The 10 Worst Resume Mistakes to Avoid
- Typos and Grammatical Errors. ...
- Lack of Specifics. ...
- Attempting the "One–Size–Fits–All" Approach. ...
- Highlighting Duties Instead of Accomplishments. ...
- Going on Too Long or Cutting Things Too Short. ...
- Bad Summary. ...
- No Action Verbs. ...
- Leaving Off Important Information.
Leave off details such as height, weight, birth date, age, sex, religion, political affiliation, or place of birth. Employers shouldn't make employment decisions based on these factors, and they may resent the fact that you are tempting them to do so. Keep your resume focused on the facts.
What are the common mistakes of a resume? ›
What impresses employers on a resume? ›
11 Common CV Mistakes According to Employers
- Having spelling errors and bad grammar. ...
- Exaggerating the truth. ...
- Poor formatting. ...
- An unoriginal personal profile. ...
- Not focusing on your achievements. ...
- Making your CV too long. ...
- Putting the wrong contact information. ...
- Not tailoring your CV to the specific role.
Which part of the resume should stand out the most? ›
- An organized layout is VERY important.
- Put format first.
- Triple-check spelling and grammar!
- List experience in chronological order.
- Identify your achievements: Challenge, actions, and results.
- Show leadership.
- Incorporate statistics.
- Use words such as achieved, created, and influenced.
What SQL skills are needed for data analyst? ›
5 Ways to Make Your Resume Stand Out
- Respond Directly to the Job Description. ...
- Describe Accomplishments, Not Responsibilities. ...
- Quantify Your Accomplishments. ...
- Use the Summary Section for Distinguishing Details. ...
- Ignore Irrelevant Information.
Programming Knowledge: As an SQL Data Analyst, one must be fluent in writing scripts, and queries and must know other Programming Languages as well. Advanced Computer Skills: The job role of a SQL Analyst also requires advanced computer knowledge. They must have basic knowledge of the hardware of computers.
What are the four main types of data analyst? ›
Four main types of data analytics
- Predictive data analytics. Predictive analytics may be the most commonly used category of data analytics. ...
- Prescriptive data analytics. ...
- Diagnostic data analytics. ...
- Descriptive data analytics.
Since almost all data analysts will need to use SQL to access data from a company's database, it's arguably the most important skill to learn to get a job. In fact, it's common for data analyst interviews to include a technical screening with SQL. Luckily, SQL is one of the easier languages to learn.
What are the 5 data analytics? ›
At different stages of business analytics, a huge amount of data is processed and depending on the requirement of the type of analysis, there are 5 types of analytics – Descriptive, Diagnostic, Predictive, Prescriptive and cognitive analytics.
What are the 5 data qualities? ›
There are data quality characteristics of which you should be aware. There are five traits that you'll find within data quality: accuracy, completeness, reliability, relevance, and timeliness – read on to learn more.
What are the 3 V's of big data analytics? ›
Dubbed the three Vs; volume, velocity, and variety, these are key to understanding how we can measure big data and just how very different 'big data' is to old fashioned data.
What are the three 3 kinds of data analysis? ›
There are three types of analytics that businesses use to drive their decision making; descriptive analytics, which tell us what has already happened; predictive analytics, which show us what could happen, and finally, prescriptive analytics, which inform us what should happen in the future.
How can I be the best stand out candidate as a data analyst? ›
As a standout data analyst you will need effective communication skills in order to present the reports you have made, some of the people you present to may not understand the technical jargon, so you should be able to explain your analysis to non-technical people.
Which personality type is best for data analyst? ›
The average Data Analyst is likely a natural problem-solver: Perceptive, analytical, and detail-oriented. The average Data Analyst tends to be confident and insightful, enjoying deep discussion to understand a particular issue.
How do I organize my resume 2022? ›
How do you write a resume in 2022 for beginners? ›
We recommend structuring your resume as follows:
- Contact Information.
- Resume Summary or Objective.
- Work Experience.
- Optional Sections/Education.
- Education/Optional Sections.
What does a good resume look like in 2023? ›
How To Make A Resume
- Choose the Right Resume Format.
- Add Your Contact Information and Personal Details.
- Start With a Heading Statement (Resume Summary or Resume Objective)
- List Your Relevant Work Experience & Key Achievements.
- Reference Your Education Correctly.
- Put Relevant Skills That Fit the Job Ad.
For the majority of job-seekers, the best resume format in 2023 is the reverse-chronological resume format. This resume format involves listing your resume information (e.g. your work experience and your education) starting with the most recent one and going backward through relevant jobs, degrees, or qualifications.
Remember, since objectives aren't required now, most people skip them. If you have the only objective in a sea of resumes, it just might help.
What are the 3 important things on a resume? ›
What are the 5 key parts of a resume? ›
Key Elements of a Resume
- Personal Information. Name Current and Permanent address (may be omitted from a resume posted on the web) ...
- Objective. In one short sentence summarize your goal for your job search. ...
- Education. ...
- Work and Related Experience. ...
- Awards and Honors. ...
- Activities/Hobbies. ...
- Skills. ...
- References (3-5 people)
The key parts of a resume are your contact information, resume profile, work history, skills, and education. You can add extra elements such as languages or certifications.
What are the best resume starters? ›
Start by listing your current or most recent role first, then list any previous work experience below. After your work experience section, include your education, relevant skills and any other relevant information such as certifications, volunteer work, student activities or courses.
What should the first sentence of a resume be? ›
There are basically three options for opening your resume: an objective statement, a summary statement or an offering statement. An "objective statement" explains, usually in one sentence, what you're seeking in a job as a job applicant. It briefly describes your personal interests.
How long should a resume be for 11 years experience? ›
Customize your resume for the job you're applying for and include only relevant experience. If you've done everything right, you shouldn't get past one page. If you have 10-15+ years of experience, it's okay to write a 2-page resume as long as all the information presented is relevant to the job.
What do employers want to see on a resume 2023? ›
Can a resume be 2 pages? ›
6 Resume Trends to Follow for Success in 2023
- Learn to articulate your skills. ...
- Personalize your resume. ...
- Show results, not just skills. ...
- Skip the fancy design elements. ...
- Use job ads to identify gaps in your skillset. ...
- Demonstrate a steady work history.
Can a Resume Be 2 Pages? A resume can be two pages, but most should be one page. That's true for entry-level candidates and those with less than 5 years' experience. If the job requires Elon-Musk-level accomplishments, or you can't cram your achievements on one page, write a two page resume.
Which of the following should not be on your resume? ›
There's no need to include personal information on a resume such as your social security number, marital status, nationality, sexual orientation, or spiritual beliefs.
What objectives should you not put on a resume? ›
Resume objective don'ts
- Don't use weak language. Certain words and phrases may come across as weaker than others, so consider the language you use in your objective statement. ...
- Don't include obvious examples. ...
- Don't use too much technical jargon. ...
- Don't forget to proofread.