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Data Analyst Resume Example & Writing Guide

A proven job specific resume example + writing guide for landing your next job in 2022. You can edit this Data Analyst resume example to get a quick start and easily build a perfect resume in just a few minutes. Just fill in your details, download your new resume & start your job application today!
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Data Analyst  Resume Example & Writing Guide
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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. They need people who have the tools and mindset to cut through the data set – who can collect it, analyze it, identify patterns and gain insights from it, and report results that point to the correct actions. These people are data analysts (and data scientists) and they are currently in huge demand.

One aspect of the demand is that there aren’t enough of them. It is almost enough to write “Data Analyst” at the top of your resume (with a few basic qualifications and some relevant experience) and you will be guaranteed to secure a few interviews. Anyone with even a basic understanding and background in data science will get a job these days. However, to find work in an organization that puts data science at the heart of everything they do is far from an easy task. Only 5% of bigger corporations have a significant data science department and the competition to learn from and work with the best colleagues in these places is fierce. 

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.

Along with our sample resumes and builder tool, we will help you bring the data of your career to life.

What does a data analyst do?

The field of data science is developing as fast as the information technology that supports it. While rudimentary software was analyzing “pools” of data a decade ago, now megacomputers are slicing and dicing data oceans to reveal the most surprising trends. Data analysts are at the forefront of translating this data into something that businesses can use. So many businesses boast of how much data they have at their fingertips, but very few are even scratching the surface in terms of understanding the insights that it might offer. Imagine a spreadsheet with a million columns and 10 million lines. That sort of complexity requires a supercomputer to manage but it requires a super data analyst to tell their colleagues what it means.

To come up with solutions, data analysts first need to understand the nature of the problem. They need to be able to talk with their colleagues in their language, exploring the real business issues and digging into what sort of data might offer potential solutions. Collecting data is not the hard bit – you have to make sure that you are collecting the sort of data that will tell you what you need to know. 

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.

Expert tip

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.

Data analyst summary resume example

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? 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.

Expert tip

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.

Resume Example: Data Analyst Summary

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.


Employment history resume example

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.

Choosing the best resume format for a data analyst

Most data analysts will want to use the reverse chronological resume format for presenting their employment history (and educational credentials too). This means listing your current or last job first and your first job last. If your career path has led you to progressively better jobs, this will highlight your most impressive credentials at the top of the list.

Resume Example: Employment History

Data Analyst at High Stream Inc., New York
October 2013 - December 2021

  • Created data modeling standards and procedures.
  • Presented data models to business teams for review.
  • Performed detailed data validation spanning several different international projects.
  • Traveled internationally assisting with training and data management.
  • Coordinated with external company to monitor and support data integration to the company's Online Provider Directory Enterprise System.
  • Worked with complex datasets and trained new hires to work with them as well.

Data Analyst at Global Solutions , New York
September 2009 - September 2013

  • Performed in-depth data validation on data from various suppliers across the world.
  • Served as the primary contact for client service teams for several different 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.

Data analyst skills CV sample

The skills section of a data analyst CV 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.

100+ Computer skills on a resume: What to list and where to revise
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Here are a few of the skill phrases you could include in your skills section:

Resume Example: Data Analyst Skills
  • Data Process Automation
  • Data Collection
  • Analysis, Reporting
  • Data Audit
  • Trend Alignment
  • Data Sets
  • Identify Patterns
  • Computer Science
  • Problem Solving
  • Creative Insights
  • Board Recommendations
  • Programming Languages
  • Critical Thinking
  • Data Screening
  • Teamwork Skills
  • Filtering Results
  • Database Development
  • Building Data Models
  • Data Mining
  • Data Segmentation
  • People Skills
  • Presentations

Education section resume example

The education section of the resume is where a data analyst shares the classroom credentials that qualify him or her for the job. Data analysts often have a degree in mathematics, economics or data science. Training in qualifications such as statistics is also common if people have moved internally from operations or finance departments. Postgraduate degrees in data science are common. 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.

Resume Example: Education Section

Master of Data Science, UCLA, Los Angeles
August 2008 — August 2010

  • Graduated in the top of my class.

Bachelor of Computer Sciences, UCLA, Los Angeles
August 2004 — May 2008

  • Graduated summa cum laude. 

Key takeaways for a data analyst resume

  1. Data analysts are in demand but competition for the best data analyst roles is high.
  2. There is a need to demonstrate how you transform analysis into profitable action.
  3. Focus on your communication and influencing skills – translating the stats to others.
  4. Share the details of your biggest projects in an end-to-end process.
  5. Your employment history should include full details of your technical capabilities .
  6. Highlight your impact on your company — how do you individually make a difference?
  7. Make sure that you share the full details of your education and job-related qualifications.

Use resume.io’s field-tested resume templates to ensure that you’re working with a viable design and format. We’ll provide a winning look and feel — all you have to do is supply the data.

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