Data Analyst CV Examples

Every strong data analyst CV example demonstrates the candidate's skills for turning data insights into business results. It's not enough to simply list your capabilities; you need to showcase how they were used in your work experience for influencing business decisions and how they led to significant professional achievements.

In addition to results-oriented work experience descriptions, it's important for recruiters to see what tools you're familiar with as a professional working in data science and data analytics, what your work methodology is, and whether you're capable of communicating your insights to stakeholders efficiently.

Below, you can find detailed insights for each section and aspect of a data analyst CV optimisation. Our professional CV writers implemented these guidelines in the CV samples you can use to get started.

As illustrated in our data analyst CV samples, a professional summary is the introductory section that briefly describes the most important and impressive skills and achievements. Your goal is to grab readers' attention and make them want to keep reading. To achieve that, make your data analytics expertise clear right away and back it up with some big wins.

Professional summaries are sometimes called CV objectives, but the term is considered outdated. That said, there are some situations where you can say what type of role you're looking for and what you're passionate about, such as when you're just entering the job market.

A data analyst CV example always lists a diverse set of skills. Besides the technical skills like SQL, Tableau, Power BI, Excel, and databases, such as PostgreSQL and BigQuery, it's equally important to highlight your "softer" skills. Those are not purely technical, and they are often interpersonal. A good example is your communication skills, which are essential for a professional working in the field of data analytics and data science.

When unsure which skills to list, read the job requirements carefully, as they almost always list all the necessary skills for the job.

Optimising the keywords for a data analyst's CV is crucial, especially for getting past applicant tracking systems (ATS). Many companies use ATS platforms in their hiring processes, and they serve as an initial filter in the selection process. Similar to recruiters, those machine readers look for specific keywords to determine whether you're a good fit for the job.

The keywords for a data professional are predominantly the skills required for the position you're applying for. Make sure to weave them into both your job descriptions and the dedicated skills list, like in our data analyst CV examples.

As we mentioned in the previous section, many companies use ATS platforms in their selection process, and among the most commonly used are Greenhouse, Lever, Workday, and iCIMS. An ATS-friendly data analyst CV example is not only one that includes all the necessary keywords.

In addition to including the keywords, you need to make your CV easily scannable by ATS. That means using standard section headings, such as Professional Summary, Work Experience, Skills, Certifications, and Education. Also, you should avoid using tables or graphics, as they can create a risk that the content of your data analyst CV won't be parsed correctly.

For data analytics and data science CVs, sticking to standard, more conventional CV formats and layouts is typically the safest option. Unless it's clear from the job posting that a creative expression would be appreciated, we recommend avoiding excessive colour and visual elements.

As a professional working in the data field, it's essential to make your skills and accomplishments the focus of your CV, without visual distractions. Additionally, choose standard fonts for a design analyst CV, such as Arial, Calibri, or Helvetica.