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Professional Data Analyst Resume Examples & Guide for 2021

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Volen Vulkov Avatar
Volen Vulkov
8 minute read
Updated on 2021-01-14

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

Ph.D. in Human-Computer Interaction in love with Electronic Music and Astronomy

+359 88 888 8888



The Hague, Netherlands
Postdoctoral Researcher
Torphy2017 - 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
Nader10/2012 - 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
Padberg8/2013 - 10/2013
San Francisco, USA
Worked on improving workers experience on Padberg 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.
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.
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.
data analyst resume layouts
  • 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



Seattle, WA
Fareed Markney
Data Analyst

+359 88 888 8888


Seattle, WA

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.

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

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?

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.

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?

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.

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:

Operations Data AnalystCompany Name
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