The best decisions are made after a careful consideration of the data: in a world where data is literally everywhere (both visible and hidden), this can sometimes overwhelm even the most experienced business leaders. You may think that demand dictates that simply being a data Analyst is enough to secure a few interviews, but to get interviews for the jobs you truly want, you need a data analyst resume that excels.
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Entry Level Business Analyst
Data Scientist
Data Engineer
Web Analyst
Business Intelligence
What makes the difference? A resume with a clear message and strong action statements.
As an analyst, you’re uniquely positioned to make the most of the information within the job listing and through research of the company and role to understand what your dream employer is looking for – and give it to them within your business analyst resume. That will get you closer to your goal: the all-important interview.
Resume guide for a data analyst resume
Anyone with even a basic understanding and background in data science will get a job these days, but you don’t want any job, you want the job. Resume.io will lead you on the path to success with our guides and resume examples for more than 500 professions, and our easy-to-use resume builder.
This resume guide seeks to explore how the various aspects of the most successful data analysts can be integrated into a resume that presents them as far more than just “number crunchers.” This guide will show you how to:
- Demonstrate how your data analyst skills would fit in with the best in the business.
- Explore how your data analysis methods have led to real-life business transformation.
- Ensure that the resume basics are covered to get past the ATS software.
- Help you to focus on your people skills as well as your spreadsheet skills.
- Choose the best resume layout to highlight your message.
Along with our sample resumes and builder tool, we will help you bring the data of your career to life.
How to write a data analyst resume
The first important data you need when writing your resume is understanding what sections to include. Your CV should contain the following elements:
- The resume header
- The resume summary (aka profile or personal statement)
- The employment history section
- The resume skills section
- The education section
The data analyst resume therefore needs to showcase an individual's broader business acumen. Without that, it will be like being lost in an endless apple orchard, unsure of which tree to shake to get the apples that you need.
While the data analyst resume should be written for a broader business audience (as the end hiring manager will often be a senior non-tech specialist), candidates should not forget to include all the details of obscure programming languages and fiendishly difficult projects for their future bosses and colleagues.
Project management skills are another important aspect of data scientists' role. Data analysts often work in groups of professionals from other departments and need to lead from a technical (if not an organizational) point of view. Their ability to identify patterns and interpret the data can then be translated into real-world actions by the specialists involved, and the end product is a true team effort.
A lot is said about tailoring a resume toward a particular employer, and a data analyst's resume is no different. If you can talk about the sorts of projects that your future employer will be considering, you automatically position yourself as someone who is a great match. Employers are looking to feel comforted when they read a resume, and if even a non-technical person can see that your experience is similar to what the company needs, you already have an advantage over your rivals. A data analyst’s resume needs to give companies the confidence that s/he is the person to identify these trends and insights.
How to beat the ATS
Data analysts understand better than most that a piece of software (or algorithm) is only as good as what it is programmed to do. Given the high numbers of applications in the recruitment process, organizations use software called Applicant Tracking Systems (ATS) to sift through the initial applications. If certain resumes do not include enough of the required keywords, it means that some highly qualified candidates can miss out and not have their resume read by a human at all. Make sure you include the words that these employers are looking for.
Read the job description to determine what the employer is looking for in terms of key skills. The ATS will often use the job description as a template to scrape keywords from, so make sure there are enough similarities between the job listing and your resume.
One method of organically getting in those keywords to combine phrases from the job listing in your summary. For example, your prospective employer wants at least 5 years of experience, expertise in statistics and mentions the programming languages Scala and MATLAB. The ad also has a “nice to have” of data visualization knowledge. You could write:
Data analyst with 5+ years of experience and master’s degree in statistics. Expert at presenting data visualizations, and proficient in Scala and MATLAB.
What is the best resume format for a data analyst?
Most data analyst resume samples will use the reverse chronological order format for presenting their employment history (and educational credentials too). This means they list the current or last job first and first job last. This works because recruiters want to know what you’ve done lately.
If your career path has led you to progressively better jobs, this will highlight your most impressive credentials at the top of the list. Other formats may suit you better if you have not walked a straight path as a data analyst or if you are entering the job market for the first time. A hybrid format balances the skills section with your work history and education and a functional format puts your skills in the forefront.
Choosing a format is simple with the many resume templates contained in our resume builder. Study all the available formats as resume examples before deciding on the one that works best for advancing your career.
Create a data display with your contact information
There’s little point in a resume for a data analyst (or anyone else) without the contact information that allows recruiters to get in touch to schedule an interview. The header is that showcase, and it adds a bit of design to your text-heavy page.
Although you want to be eye-catching, you need to ensure that above all your data is easy to read. Standard information to present:
- Name. Both first and last. You may use a middle initial if you have a common name.
- Title. Repeat the title from the job listing and make sure you personalize it for each position if the titles are different.
- Email address. Keep it professional with a [email protected] format or similar.
- Home address. List only your city and state. Include “ Willing to relocate” if that is the case.
- Social media or portfolio. Use LinkedIn if you have kept it updated or link to your portfolio (our resume builder makes this a cinch) or other professional examples such as a website of your work.
No other information is necessary.
Highlight your best in your summary
The summary for a data analyst should focus on three things: industry expertise, business acumen and project wins. Do you know your stuff, is it useful to people around you and will your smarts make your employer more profitable? Show it with examples of your accomplishments.
Your summary needs to highlight how you are different from all other candidates, who will likely just be coming up with a long list of their analytical skills. When you talk about your role as a conduit between the data and your colleagues, you showcase your true value. When you talk about the impact of your projects on the direction and profitability of your company, you quantify your mad data skills in real terms.
If you don’t talk about how you collect and analyze data in your summary, your prospective employer will be suspicious. Don’t let your business acumen overshadow your core talents as a data analyst. Talk about the problems you have solved, the scale of the data you have worked with and the software that you use.
But data doesn't live in a vacuum. All data analysts have their own approach to communicating data to their colleagues and getting others on board with what it means. It is important to describe exactly how you make your data come to life, because it won’t do much good stuck on a spreadsheet that only you can understand.
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Put other people in your summary
A data analyst’s output does not come without a great deal of input from others. Data analysts present their findings to their colleagues, discuss what they might mean, take into account feedback to refine their models, and build new hypotheses based on all the evidence. They might understand the data at a deeper level than those around them, but that doesn’t mean those around them understand the data from a different angle. It is only by working together that the optimal path forward is found.
You can find adaptable data analyst resume example summaries below:
Recent graduate with strong academic background in statistics and machine learning, eager to begin data analyst career. Adept at interpreting and analyzing complex datasets using MySQL to support data-driven decision-making. Proficient in statistical modeling and data visualization using Python and Excel.
Experienced and dedicated Data Analyst with several years of experience identifying efficiencies and problem areas within data streams while communicating needs for projects. Adept at receiving and monitoring data from multiple data streams, including Access, SQL, and Excel data sources. Ability to synthesize quantitative information and interact effectively with colleagues and clients. Proven track record of generating summary documents for senior management for monthly and quarterly audit and compliance reporting.
Accomplished data analyst with wealth of experience in strategic decision-making and leadership that create efficiencies throughout businesses. Proven expertise at leading cross-functional teams, developing and implementing robust analytical solutions, and translating complex findings into actionable strategies
Create a roadmap of your data analyst experience: let data drive your text
As a data analyst, your employment history needs to focus on the detail of what your data analytics work has achieved. It is no good talking about what skills you have without sharing the outcomes of those skills. Stick with the key projects that are likely to be relevant for your future employer and include more detail for your most recent employers.
Data science has moved on significantly in the past four to five years, so experience from your earlier career will be less relevant. Show your progression in terms of the scale of projects that you have been entrusted with and the complexity of the data you have worked with. If you are doing a detailed description of a situation, you might consider using the STAR method, where S is the situation you were in, T is the task you faced, A is the action you took and R is the result you achieved.
As a data-driven decision-maker, you know the importance of including all the relevant results-based points. The more detailed you can get, the better. For example:
- Performed deep statistical analysis using R to enhance understanding of customer behavior leading to 12% in sales leads.
- Created interactive data model that allowed marketing department to visualize impact of of shifting demographics and hone micro-campaigns for cost savings of $50K a quarter.
- Collaborated with client services team to pinpoint best data modeling and presentation resulting in 97% client retention three years running.
Take a look at the data analyst employment history resume sample below:
Data Analyst at High Stream Inc., New York
October 2013 - Present
- Create data modeling standards and procedures.
- Present data models to business teams for review.
- Perform detailed data validation spanning several different international projects.
- Travel internationally assisting with training and data management.
- Coordinate with external company to monitor and support data integration to the company's Online Provider Directory Enterprise System.
- Work with complex datasets and train new hires to work with them as well.
Data Ananlyst at Global Solutions , New York
September 2009 - September 2013
- Performed in-depth data validation on data from various suppliers around the world.
- Served as primary contact for client service teams for several projects.
- Researched and resolved data discrepancies with troubleshooting teams.
- Merged data with existing data sets, careful to keep old data sets and documentation.
- Provided tutorials on current data management techniques including assisting with analysis and providing technical recommendations on study software.
- Communicated effectively with project management regarding issues and needs for projects.
Help visualize your data analyst expertise with a curated skills section
The skills section of a data analyst resume is where an employer will expect every data science box to be ticked. If there are certain aspects missing, alarm bells will ring, so make sure that the list is as comprehensive as possible.
Here are some of the areas that we would expect to be present in the top tier of candidates: They use the most advanced methods to collect their data, automating processes to allow them to interpret and analyze behaviors. With the assistance of data extraction software, they are able to explore the data, identify patterns and build testable models. When they look at the resulting data sets, they can form links and draw conclusions for the wider business.
Their mathematical and analytical skills need to be advanced in order to see these patterns, but it is actually more important to be able to translate these findings into simple and understandable actions for their colleagues to take. This requires creative thinking and artistic license.
Here are a few of the data analyst resume example skills you could include in your skills section:
Key skills and proficiencies
Detail your education & relevant data analyst certifications
The education of a resume for a data analyst is where you share the credentials that qualify you for the job. Data analysts often have a degree in mathematics, economics or data science. Postgraduate degrees in data science are also common.
Those who have moved from the operations or finance department may also have training in qualifications such as statistics.
Given the need for a broader business outlook, MBAs are also welcomed by many employers. It is common to detail all knowledge of programming languages and data software in the education section and the more that you can include, the better.
Certifications also boost your candidacy. For example, Coursera offers data analytics certificates for Google, IBM, Microsoft, AWS and SAS. If you have at least a few, and the space in your data analyst resume, you may create a separate section to highlight these.
Master of Data Science, UCLA, Los Angeles
August 2008 — August 2010
- Graduated in the top 5% of my class.
Bachelor of Computer Sciences, UCLA, Los Angeles
August 2004 — May 2008
- Graduated summa cum laude.
Opt for the right visualization for your data analyst resume
One key aspect of your job is data visualization so any exemplary data analyst resume example will take into account the presentation of your career data. A professional look makes your argument for employment all the more compelling and signals that you can present data persuasively.
Finding the right side of the line dividing professionally memorable and overly busy is easy with one of our field-tested resume templates. They ensure the fonts you use are legible, the sizes and proportions balance and, if you choose to get colorful, that you don’t get carried away.
Our creative resume templates may be the choice for you if you specialize in presentations. Or, show you’re of the times with a modern data analyst resume layout.
Data analyst job market and outlook
You chose a high-growth field – in fact, it’s the third-fastest growing field at an expected 35% increase in demand over the next decade. As businesses lean more heavily on data to inform decisions and the methods of crunching that data improve, opportunities will expand with them.
- The data analytics market is projected to grow from $7.03 billion in 2023 to $303.4 billion in 2030.
- 15% of jobs in data analytics jobs are in IT services and consulting.
- There are expected to be 59,400 more data science jobs in 2032 than there are today.
What salary can a data analyst expect?
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Key takeaways for building a data analyst resume
- Data analysts are in demand but competition for the best data analyst roles is high.
- Focus on your communication and influencing skills – translating the stats to others.
- Share the details of your biggest projects in an end-to-end process.
- Your employment history should include full details of your technical capabilities.
- Highlight your impact on your company — how do you individually make a difference?
- Use resume.io’s field-tested resume templates to ensure that you’re working with a viable design and format.
