A Guide to Using Data Analyst Resume Keywords

By Indeed Editorial Team

Published 20 June 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

A data analyst uses a range of information to identify patterns and suggest improvements for businesses. When applying for a job as a data analyst, it's important to identify and use relevant keywords on your resume to increase your chances of progressing through the recruitment stages. Learning more about using keywords on your resume for a data analyst job can help you include them effectively. In this article, we discuss what data analyst resume keywords are, explore their importance, explain how to include them on your resume, share a list of relevant keywords and offer some general resume writing tips.

What are data analyst resume keywords?

Data analyst resume keywords refer to the unique education, experience, skills and attributes recruiters seek in data analyst candidates. These keywords are usually descriptive job-related nouns that describe your suitability for the role. They can also be a combination of nouns and verbs that showcase your past accomplishments or experience. Because of this, an Applicant Tracking System (ATS) commonly in use by many recruiters may scan keywords and key phrases when shortlisting resumes for review.

Related: What Does a Data Analyst Do? (With Skills and Career Steps)

The importance of using resume keywords

Ultimately, using relevant keywords on your resume is important because it can demonstrate relevance and suitability to attract recruiters' attention. When hiring a data analyst, recruiters may receive hundreds of resumes. Because of this, they often use an ATS, also known as resume-scanning software, to determine which resumes to review. Recruiters can designate important keywords for the software to look for in the resumes it scans. Regardless of whether an ATS is in use, identifying important keywords and ensuring your resume highlights them is one way you can increase your chances of gaining an interview.

Related: What Makes a Good Resume?

How to include data analyst keywords on your resume

These are the steps you can follow to target keywords in your data analyst resume:

1. Review the job advertisement

One of the best ways to identify relevant keywords is to review the job advertisement, specifically the job description section. You can look for words or phrases that appear more than once or are in bold or italics. It's a great idea to read through the job advertisement thoroughly and list any keywords you come across that a resume-scanning program or hiring manager may look for.

2. Identify keywords that match your employment attributes

Once you've compiled a list of relevant keywords, determine which of them overlap with your qualifications, experience and skills and include those on your resume. It's a good idea to maintain a genuine report of your employment attributes to avoid referring to keywords that highlight attributes you don't possess. For example, the job description may include the keywords technical writing, coding and master's degree. If you're proficient in technical writing and coding but don't have a master's degree, you can choose to focus on the mentioned skills and provide an accurate representation of the education you have.

3. Highlight the relevant keywords

It's important that you highlight the keywords on your resume. You can do this by using some of them in your professional summary and listing others first in your skills or qualifications section. You can also consider altering your language to better fit keywords. For example, if a keyword is a high level of attention to detail and your resume lists attention to detail, consider altering it to be an exact match. It can be beneficial to mention the relevant keywords in your cover letter or other documents that accompany your application, too.

4. Ensure your resume reads well

When you have completed including the keywords on your resume, it's important to ensure the resume reads well and has a natural flow. During this process, you may identify better places to insert various keywords or notice keywords you forgot to include. It can be beneficial to ask a family member, friend or colleague to proofread your resume for you with a focus on natural-sounding language.

Related: How to Create a Stand-Out Resume (With Template and Example)

Keywords for a data analyst resume

While every job description may have its own unique set of keywords, below, you can find some common data analyst keywords and key phrases that recruiters often include in job descriptions and look for on resumes:

  • data

  • data analysis

  • analysis

  • data analytics

  • analytics

  • data visualisation

  • data management

  • statistics

  • statistical analysis

  • business

  • data mining

  • organisation skills

  • time management

  • team player

  • mining

  • modeling

  • machine

  • experienced

  • Python

  • R

  • Microsoft Access

  • Tableau

  • MySQL

  • programming languages

  • coding

  • Microsoft Excel

  • critical thinking

  • productivity

  • attention to detail

  • communication skills

  • bachelor's degree

  • computer science

  • technology

  • proven track record

  • accuracy

  • full-time

8 resume writing tips

You can use the tips below to guide you on your resume creation:

  1. Review the hiring company. By reviewing the hiring company, you can get to know more about what it is, what it does and what it values. It's a good idea to ensure your resume aligns with the company's objectives and culture.

  2. Review other data analysts' resumes. Finding and reviewing data analyst resume samples online can help you optimise your own. You can gain inspiration from their use of language, skills, job responsibilities and accomplishments.

  3. Use a professional email address. When supplying your contact information on your resume, it's helpful to use a professional email address that's not your current work email address. Consider using a professional email address that's a combination of your first and last name.

  4. Keep your professional summary brief. Your professional summary is a chance to sell yourself to the recruiter and encourage them to read the rest of your resume. Because of this, it's important you keep it relevant and brief so they can read and understand it quickly.

  5. Include your most desired attributes first. Try to include the information on your resume in order of importance to the recruiter. For example, if the job description emphasises the need for a bachelor's degree, but doesn't specify a desired level of experience, you can list your qualifications before your work history.

  6. Focus on quality over quantity. It can be tempting to include everything that makes you an employable individual on your resume to impress the hiring manager. Keeping your resume brief and very relevant to the position you're applying for can make more of an impact.

  7. Proofread and edit. Apart from checking that your resume flows well and reads naturally with your use of keywords, it's also important to check for spelling mistakes and grammatical errors. Proofreading and editing your resume before submitting it can enhance your application.

  8. Schedule time to write your resume. Writing an effective data analyst resume can take time. Scheduling time in your calendar for writing your resume can ensure you can give it the time and effort it requires before the application closing date.

Related: How to Choose the Best Time to Send a Resume to an Employer

Resume template for data analyst

Below, you can explore a template for writing a resume for a data analyst position:

[Full name]
[Email address] | [Phone number] | [City, State]

Professional summary
[In this section, you can summarise your key strengths in two or three sentences. This is a great section to include keywords.]

Qualifications
[Qualification name]
[Institute name], [Date of graduation]

Work experience
[Most recent job title]
[Employer name], [Employment dates]

  • [job responsibility]

  • [job responsibility]

  • [job responsibility]

  • [job responsibility]

  • [job responsibility]

[Job title]
[Employer name], [Employment dates]

  • [job responsibility]

  • [job responsibility]

  • [job responsibility]

Technical skills
[You can list your technical skills in this section, separated by pipe characters or commas.]

Soft skills
[You can list your soft skills in this section on one line, separated by pipe characters or commas.]

Related: Finding the Best Resume Template (With Tips and Examples)

Resume example for an administrative position

Below, you can find a resume example for an administrative officer's job application:

Jonas Peters jpeters@email.com.au | 042 257 3581 | Adelaide, SA

Professional Summary
Experienced leadership-oriented data analyst. Fluent in data assessment, technical writing and presentations. Possesses expert knowledge of research, data analysis methodologies and visualisation techniques. Seeking employment with an expansive data analysis team when I can contribute to leading an elite database re-engineering task force.

Qualifications
Bachelor of Computer Science

Bridgebank University, 2017

Work Experience
Data analyst
PSG Group, May 2020–May 2022

  • identified reliable data sources

  • collected, organised and analysed data

  • created data visualisations

  • developed, implemented and maintained data libraries

  • prepared reports and presentations for various projects, departments and executives

Junior data analyst
North Tech, November 2018–May 2020

  • assisted with maintaining data accuracy

  • helped develop data analysis strategies

  • created various monthly statistics reports

Technical skills
SQL | Python | Microsoft Access | Microsoft Excel | Statistical programming | Data analysis | Data visualisation | Data modelling | Machine learning

Soft skills
Leadership | Self-motivation | Written and verbal communication | Critical thinking | Attention to detail | Teamwork | Organisation

Please note that none of the companies, institutions or organisations mentioned in this article are affiliated with Indeed.

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