Data Analyst Resume Example and guide for 2019

Volen Vulkov
8 minute read

The Data Analyst job position is seeing unprecedented attention over the past couple of years.

Businesses collect copious amounts of information and this precipitates the need for a person in charge of making sense of that data.

Data analyst jobs are projected to grow by 27% (or 31,300 jobs) from 2016 through 2026, much faster than the average.

As demand for data analysts grows, the field becomes more competitive. There are many candidates competing for the same position.

The role of the resume becomes even greater in such a competitive environment.

To help you out, we will guide you how to create a high-quality professional resume that helps you get noticed and get hired.

See our hand-picked data analyst resume and link to build your own

PAVEL KUCHERbaev
Ph.D. in Human-Computer Interaction in love with Electronic Music and Astronomy
+359 88 888 8888
help@enhancv.com
http://kucherbaev.com
The Hague, Netherlands
ACADEMIC EXPERIENCE
Postdoctoral Researcher
Delft University of Technology2017 - Ongoing
Delft, Netherlands
At Web Information Systems research group I work on: 1) context-based music recommenders, 2) human aided bots (e.g. conversational agents with humans in the loop), and 3) quality control in crowdsourcing
Introduced hybrid context-based music recommender (accepted to ICML2017 workshop on Machine Learning for Music Discovery).
Surveyed human aided bots (in review at IEEE Internet Computing), and introduced a way such bots could be used in city context (accepted to RecSys2017 workshop on Recommender Systems for Citizens). Currently, I design and develop a chatbot able to self-learn new skills (to submit to WWW2018), and techniques to generate data via crowdsourcing for training NLU models (to submit to CHI2018).
Developed techniques to predict the quality of results in crowd platforms based on workers behavior (to submit to WWW2018).​
Ph.D. in Human-Computer Interaction
University of Trento10/2012 - 2/2016
Trento, Italy
At Social Informatics research group I contributed to crowdsourcing in three areas: 1) quality control, 2) workers experience, 3) complex work.
Published in CSCW2016, Internet Computing, HCOMP2015, Transactions on the Web, BPM2015, AVI2014, CHItaly2013, BPMS2012.
Together with colleagues from Milan, Sydney, and Zabol we made the most extensive review of quality assurance and assessment techniques in crowdsourcing (in review at ACM Computing Surveys).
Visiting Researcher
CrowdFlower8/2013 - 10/2013
San Francisco, USA
Worked on improving workers experience on CrowdFlower platform.
Conducted a user study about task searching (published in AVI2014).
Developed a prototype of task listing page, designed for optimising task searching experience. It was partially adopted in production.
ENTREPRENEUREAL EXPERIENCE
Cofounder & CEOUniverius SRLs
3/2016 - 11/2017
Trento / Bolzano / Milan, Italy
Cofounded and lead the company in Italy with a mission to bring the experience of watching space objects to masses.
Showed the Moon and planets via telescopes to 5000+ people.
Cofounder & CTOCodesign.io
8/2013 - 4/2016
Distributed team
Developed a web-base feedback tool for designers and developers (Python, NodeJs, Javascript/React). Lead a team of 2 developers.
Acquired 10000+ registered, 1500+ active, and 50+ paying users.
SPOTLIGHT
WHY SPOTIFY?
I am obsessed with discovering great music. According to Spotify.me I streamed 21.5 hours of music in 2 days. Working as a Research Scientist I am excited to make a positive impact on the experience I and millions of other people have during these hours.
Human-Computer Interaction
I have more than 5 years of experience, working on various HCI projects:
MUSIC RECOMMENDATION (rich-context-based music recommender system, crowdsourcing-based music tagging solution)
NLU and CONVERSATIONAL AGENTS (training data generation for NLU with crowdsourcing, NLU retraining techniques, Human Aided Bots, self-learning chatbots)
CROWDSOURCING (Ph.D. in quality control in crowdsourcing, internship at CrowdFlower)
Experiments Design
I have experience running both qualitative and quantitative studies, including:
USER STUDIES (performed multiple studies analysing workers' behaviour on Amazon Mechanical TURK and CrowdFlower)
SURVEYS (conducted various surveys, including the one about causes influencing music preferences) AND INTERVIEWS (interviewed Codesign.io users to detect "pains" in their collaboration processes)
PARTICIPATORY DESIGN (led a workshop in Amsterdam with 60+ members on how chatbots could be used in city context, which led to 10+ mockups and prototypes)
Data Science
Apart from the experience with data analysis for experiments in academic research, I have completed relevant courses on Udacity and Coursera, and now I master my skills on Kaggle. In addition:
MACHINE LEARNING (accepted to summer school about Bayesian methods for Deep Learning, led by Google DeepMind and Yandex, in Moscow in August 2017)
DATA ANALYSIS (performed an analysis of the public dataset about bike sharing in Bay Area, and introduced methods to balance the usage of bikes to decrease maintenance)

What this guide will show you:

  • Choosing the right Resume Template for your Data Analyst Resume
  • Why the Data Analyst Resume Summary or Resume Objective is so important
  • How to make your Data Analyst work experience easy to read and powerful
  • Matching your Data Analyst skills on your resume to the job opening
  • Top 10 Data Analyst certifications to include on your resume
  • The best way to show education on your Data Analyst resume
  • What Data Analyst duties and responsibilities to include in your resume
  • How to get an entry-level Data Analyst job

Not a data analyst? Check out these related resume examples:

Choosing the right outline for your data analyst resume

What should your data analyst resume outline include?

  • Objective or summary
  • Data analysis Experience
  • Education
  • Certifications
  • Technical skills
  • Data projects
  • Soft Skills
  • Interests
  • References

In your data analyst resume, it’s good to include information like certifications you’ve taken, projects you’ve worked on, and specific skills. These can be anything from handling data and using the best statistical methods to explaining what said data means. Make space for all of this in the resume outline you choose!

Choosing the perfect data analyst resume layout is easy

Resume templates differ wildly, so you will need to think carefully about the best format to present what you have to offer. Recruiters spend too little time on each resume, so your resume template will serve two main purposes:

  • Grab the attention of the recruiter, helping you stand out in a pile of other applicants;
  • Guide them through your professional experience and skills, proving you are a viable candidate they should invite to an interview.
  • Basic layout - If you’re an entry level data analyst or fresher, you’re not likely to have enough experience in the field to really fill up a resume. This single column design works well when you have less content but want it to look great aesthetically anyways.
  • Professional layout - This is a classic layout, ideal for someone who’s already got a few years of data analysis experience and is perhaps looking to move up in their career.
  • Simple layout - If you’re a senior data analyst and have plenty of relevant experience to show off, this more compact layout is ideal. It manages to fit in tons of information without looking clutters. The result is a data analyst resume that’s not showing off, but has plenty to show.
  • Creative layout - If you want a lighter and more modern feel, this layout is perfect. It shows you’re ready for the 21st century economy (you are a data analyst after all) while avoiding anything too flashy or out there. This would work well if you’re looking for a higher level position which mixes regular data analysis with management.

Here’s what you should consider when choosing a data analyst resume layout:

  • Make sure your data analyst resume is easy to read and the design naturally guides the reader through the different sections.
  • Don’t bury your greatest achievements in your experience section - make sure they stand out with a separate section in your template.
  • You might like to dedicate a separate template section to data analyst projects you’ve worked on, especially if you have little formal experience in the field.
  • Data analyst certifications are important. Include them in your resume to show potential employers you spend time constantly honing your skills.
  • Make sure you include skills that are not only related to data management, but to visualizing results and communicating them to stakeholders.

Nailing your data analyst resume header is more important than you think

Whether it’s a CTA or a regular hiring manager, the first thing someone is going to see when they look at your data analyst resume is the header.  That’s why, simple as it may seem, it’s essential to get it perfect.

A data analyst header should have the following:

  • Your name and any relevant certifications like CCA or EMCDSA.
  • Your title, this should be as detailed as possible and include details like “entry level” or “senior” if relevant.
  • Your contact info, be sure to use a professional email and add a phone number in case the recruiter needs to call you.
  • Websites showing your work, this could be a personal site, LinkedIn, or somewhere like Github. The point is to show that you post your work, collaborate, and network, all great qualities for a data analyst.
Fareed Markney, CCA
RecentGraduate and Entry-Level Data Analyst
+359 88 888 8888
help@enhancv.com
Github.com/fareedmarkneycca
Seattle, WA
RIGHT
Fareed Markney
Data Analyst
+359 88 888 8888
help@enhancv.com
Seattle, WA
WRONG

The second examples screams “phoning it in” while the first says “I’m a proud data analyst ready to show what I can do and learn.” Obviously, the second is the message you want to be sending.

PRO TIPLaws about what kind of personal information can go on a resume vary widely between different companies and countries. Be sure to check the rules where you’re applying. If you’re unsure, you can always email the HR department to ask.

Why the data analyst resume summary or resume objective is so important

The resume summary or objective can serve as a trailer to your resume - it has to get the attention of the reader and keep it.

To write an effective resume summary or objective, you need to think about your impact. What have you helped the company accomplish?

Back that information up with hard data - after all, this is something you need to do on a daily basis as a data analyst.

Summary
A motivated data analyst with relevant certifications who is eager to grow and learn.
WRONG

You can tell this one almost gets it right, but vague wording makes this sound meaningless. What makes you motivated? What certifications to you have? Of course you’re eager to grow and learn, what data analyst isn’t?

Summary
A mid-level data analyst with 6 years of experience working for Dell and The World Bank, a AWS Big Data Specialty Certification, and an MCSE in Data Management and Analytics. Currently looking for a more senior role where I can apply my data visualization experience to better understand and tackle the world’s greatest humanitarian challenges.
RIGHT

A lot gets said in just 55 words. You know their level, get a snapshot of their experience, their certifications, what they want in their next role, and even their motivations. But what if you’re an entry level data analyst?

Summary
A recent graduate of the Johns Hopkins University School of Public Health Department of Biostatistics with an ScM focusing on global health statistics looking for an entry level data science position combining my passion for data and desire to tackle the world’s greatest humanitarian challenges.
RIGHT

This resume summary strikes the perfect balance between sounding qualified and professional along with conveying a deep passion for the field.

What you should include in your data analyst resume summary:

  • An elevator pitch that presents what your value to the company will be.
  • Hard data on what your impact has been.
  • A hint about your motivation and interests.
  • Who you are and what your personal qualities are.
  • Why you’re a valuable hire.
  • What is your motivation and career trajectory.

This information will help recruiters decide if you’re a good culture fit for the company and whether or not the company can accommodate your career development dreams.

If you will be adding a cover letter to your application, you might want to expand on this information there and skip the resume objective or summary altogether. This is not a required section in your resume but it may play a role to distinguish you from the competition.

How to make your data analyst work experience easy to read and powerful

The experience section in your resume gets the most attention from recruiters. It should represent everything you’ve learned during the years you’ve spent honing your skills.

To make sure your experience section says it all, make sure you highlight a few key bits of information.

First, make sure it’s clear what was your role in the company and what industry you were working in. Then make sure you demonstrate the impact you had on the business - and back it up by numbers.

Usually we recommend keeping jargon to a minimum, but don’t shy away from some data analyst terminology. It will convince the recruiter you know your stuff, but you’re not trying to show off for the sake of showing off.

Data analyst resume experience examples:

Experience
Operations Data AnalystCompany
06/2017 - 09/2018
Buffalo, NY
Used SQL, Tableau, and Cloudera to compile monthly 40+ page summaries of company operations, identifying key areas for improvement to senior management
Identified a supply chain optimization which, when implemented, saved the company $1.2 million in annual costs due to a reduced risk portfolio and more on time deliveries
Led the company push to successfully become GDPR compliant before the regulatory deadline, preventing a potential disruption in EU operations
RIGHT
Experience
Operations Data AnalystCompany
06/2017 - 09/2018
Buffalo, NY
Used a variety data software for complex visualization
Identified and analyzed new market opportunities, reporting them to superiors at weekly meetings
Met all of the relevant data protection standards
WRONG

See the difference? The second example is vague and focuses on responsibilities. It could be used to describe the exact same experience as the first example, but the impression you get as a reader is dramatically different.

Say, you’ve worked on improving the data infrastructure within the organization. Rather than saying “Headed the internal data systems overhaul” (which is already better than what most candidates write because of the strong verbs you’re using) you can write what this led to.

Did it lead to a 10% improvement of the time for information retrieval? Did the easier process increase the adoption of regular data checks by other teams? Whatever the result was, add it - and best try to quantify it!

What makes data analyst resume experience effective:

  • As a Data Analyst, you must be concise and clear - so make your bullets specific and to the point.
  • Use numbers to demonstrate your impact - be specific and show your achievements.
  • Use keywords and data science terminology to show you’re proficient in the field.
  • Don’t opt for the easiest vocabulary - use active verbs, strong and uncommon words.
  • Frame any experience in lessons learned and skills gained that will help you for this job.
PRO TIPTo leave an impression and stand out, make sure you use active verbs. For example, rather than saying “led the development of the internal data structure in the company”, change that verb to “spearheaded” or “oversaw”. This will make your resume experience section much better.

What should an entry level data analyst resume experience section look like?

You may have read that last section and thought “yes, but I don’t have any experience like that in my past, what should I do?”

Not to worry, you can show you have relevant experience in other ways.

  • Start by identifying all of the relevant skills from the job description (a detailed breakdown on how to do that under the Skills section below on this page).
  • Find ways to show you have those skills in other jobs, projects, or education. For example, if they want presentation skills you can mention your university debate experience. Or, if they want someone adept at SQL, show that you got a free online certification.

The best way to show education on your data analyst resume

A data analyst position will often require at least a bachelor's degree in business analytics, data science, computer science, or a similar field that’s highly reliant on statistics.

If you don’t have that, but you’ve still taken a statistics course or two, don’t despair. Just make sure to highlight that information in your education description.

Here’s what you should do to optimize your data analyst resume education section:

  • Include your highest education degree first;
  • Highlight any math or statistics courses you’ve taken;
  • Mention specific tools or database query languages you’ve worked with that also appear in the job description;
  • Add anything that puts you in front of the pack - be it classes you took, honors and awards, or a capstone project that contained a strong analytical element.

Here’s an example of an education section for a senior data analyst:

Education
ScM, Global Health StatisticsJohns Hopkins University School of Public Health
2005 - 2009
GPA
4.0 / 4.0
RIGHT

Because this person finished their degree a decade ago, there’s no need to include any details beyond the basics. Their 10 years of work experience should speak for itself.

An entry level data analyst education section should look more like this:

Education
ScM, Global Health StatisticsJohns Hopkins University School of Public Health
2015 - 2019
Specialised in Biostatistics
Final project was a 64 page thesis on how to better use statistics to understand poverty in East African states with limited access to data
Worked with Professor Miller on a trip to Somaliland to consult with local ministers about accurately gathering and analyzing information about local economic conditions
GPA
4.0 / 4.0
RIGHT
PRO TIPIf your education wasn’t related to the data analytics field at all, you might want to skip this section altogether - instead, make your certifications the center of attention. During the interview phase you will be able to explain why you transitioned to data analytics if your formal education was in a different field.

What skills should your data analyst resume include?

A data analyst needs to have both hard mathematical and statistical skills, as well as soft skills that come into play when you present your findings or present business issues to different business stakeholders.

Of course, you’re going nowhere if you don’t have the technical skills. After all, as a data analyst you’ll be handling large amounts of information on a daily basis.

How to show your technical skills

Most technical skills can simply be listed this way (unless you have certifications for them, in which case you should include that in your certifications section). This section allows the reader to see your strengths at a glance. The rest of your resume can go into more detail about what you’ve accomplished applying these skills.

What technical skills should your data analyst resume have?

  • Analytical skills: descriptive, inferential, and predictive statistics;
  • Math skills;
  • Data cleaning;
  • Advanced Microsoft Excel knowledge;
  • SQL and other database querying languages;
  • Tableau and other data visualization tools;

In terms of analytical skills, data analysts are usually required to have a good grasp on descriptive and inferential statistics - letting them spot customer habits, valuable segmentation criteria and other key business information.

As far as technical skills go, there is a growing requirement for data analysts to be proficient in database querying languages. Most businesses work with SQL, but there are some other options out there. In any case, learning the logic behind SQL will help you build queries in other languages, too.

As many businesses are adopting Tableau, it’d be good to familiarize yourself with this powerful data visualization tool. It is crucial when you need to present information to different teams in the company - or even when you’re trying to make sense of the data yourself.

How to effectively include soft skills on a data analyst resume

Technical skills are not all. Actually, recruiters seem wary of hiring a strong technical candidate who’s expecting that their role will be similar to a software engineer, and won’t be effective when communicating with other business stakeholders.

That’s why it’s good to highlight your communication skills, too. Just make sure that rather than writing a hollow “excellent communicator”, you actually mention a situation that proves your communication skills.

Top Skills

Skills
Creative Problem SolvingWhen accurate birth records weren’t available in Somaliland, I developed a statistical model which provided estimates based on neighboring regions and sale of products associated with infants.
Attention to DetailWorked part time as an editor during university, going through hundreds of pages of technical writing to discover errors and improve readability.
Presentation and CommunicationI’ve made 4 presentations at international conferences based on my research
RIGHT

Here you can see how a data analyst can not just list vague soft skills but effectively back them up with examples.

The most important data analyst soft skills to include:

  • Working well in teams
  • Communication skills
  • Creative problem-solving
  • Attention to detail
  • Ability to meet deadlines
  • Organization

Matching your Data Analyst skills on your resume to the job opening

Any resume should be tailored as much as possible to the specific job it’s being used to apply for.

To show you just what this looks like, here’s some text taken from an actual data analyst job posting on Indeed.com.

  • Oversee the collection and analysis of due-diligence data, including results of the FLA's Sustainable Compliance Initiative (SCI) assessments and fair compensation program. Analyze trends and connect data across projects and departments.
  • Present analytical results and data visualizations in a way that is meaningful for stakeholders and provides actionable insight. Design and prepare reports and presentations in support of the FLA's strategic goals.”

Let’s see what those key words highlighted above should translate into on your resume.

Oversee: You’re going to need to show management and leadership skills. Try and include examples of times when you’ve demonstrated those qualities in your experience section.

Analyze trends: You’re going to be expected to conduct analysis, no surprise there, but be sure to use this same kind of language when describing your analyst experience.

Across projects and departments: You’re not going to be working in a bubble. This tells you that you need to show that you work well in complex organizations and can communicate effectively with people who may have a very different knowledge base than your own.

Present: Presentation skills are important, try and mention them where possible.

Meaningful for stakeholders: You need to show that you can use empathy to understand what’s important to others.

Actionable Insight: Show that you can think beyond your own work to how it’s going to be used by others in an organization to change things.

Design and prepare: You’re going to be expected to manage reports including their visual style. It would be great to emphasize any familiarity with design.

As a data analyst, you should already be used to doing this kind of deep analysis. Just think of the job description as a mountain of data you need to draw the right conclusions from.

Top 5 skills on data analyst resumes vs job offers

Because we believe in the power of big data, we conducted an analysis of over 100,000 resumes and job descriptions on Indeed.com. The goal was to understand what skills were the most in demand by comparing which skills were commonly listed on resumes vs those that were commonly listed on job descriptions.

The graph below can show you what skills are most in demand (a demand that’s not being met by current data analyst job applicants).

Top 10 Data Analyst certifications to include on your resume

  1. Cloudera Certified Associate (CCA) Data Analyst
  2. EMC Proven Professional Data Scientist Associate (EMCDSA)
  3. MapR Certified Data Analyst 1.9
  4. Certification of Professional Achievement in Data Sciences – Columbia University
  5. Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics
  6. Udacity Data Analyst Nanodegree
  7. Coursera Johns Hopkins Data Science Certification
  8. INFORMS Certified Analytics Professional
  9. Amazon Web Services Big Data Specialty Certification
  10. Data Science Certificate - Harvard University

There’s a big skills gap in the data science field is big. AMcKinsey Global Institute study states that the U.S. faces a shortage of 1.5 million managers and analysts who can understand and make decisions using big data.

And since this is a newly emerging field, university education is on par with additional certifications you can take. The certifications we mentioned above are useful for every data analyst - but especially if you’re transferring to data science from another field.

On the one hand, a certification testifies to your data analyst skills and experience. On the other, the projects you work on as part of your certification provide a proof of concept which you can showcase during recruitment interviews. You can also include these in a separate Projects section in your resume.

Other sections to give your data analyst resume that something extra

Besides everything mentioned above, there are a few final sections you may want to consider. One is projects. If you have data analysis projects that were outside of your education or formal work experience, this is a great section to show that experience.

Also don’t be afraid to include a little personality. As the job description mentioned above showed, data analysts are expected to have excellent personal skills. Therefore, showing some personality on your resume is vital.

Take a look at the company or organization’s website in addition to the job description. What personal qualities do they emphasize in their company culture in addition to the job? Now think about how you can show you’ll be a great fit.

This can be done by including your interests, or simply things you’re most proud of. You can also include sections of your favorite books, professors, or thinkers in the field which have shaped how you approach data science and statistics.

All of this goes a long way to letting you stand out from the crowd and demonstrate you’ll be more than just a data analyzing robot.

What will make your data analyst resume great? In summary:

  • Concise and specific information about your responsibilities and impact.
  • Overview of your data analyst experience and education that is tailored to the job description.
  • Skills, both technical and soft ones matter.
  • Certifications and online courses you’ve taken to extend your education.
  • All of this should be presented in a clean modern resume template.

Although the data science field is very competitive, you’ll maximize your chances to land a job when you pass the first hurdle - getting an interview. A carefully planned resume will do just that.

The best data analyst resumes contain no fluff and are focused to present all key information your target audience - the recruiter - needs. It is not just an application documents - it also shows how good you are to provide concise information and insights. Something you will be doing on a daily basis once you get hired.

So make sure you prove you’re good at it, starting with the resume!

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