How to write a data analyst CV

With the amount of data being created and stored growing exponentially, the opportunities for data analysts and data scientists to manage, analyse and interpret this across all sectors of the economy are immense. With competition for jobs growing, the need for a CV that helps set you apart is vital.

Put yourself in the shoes of the recruiter

Before you start writing or refreshing your data analyst CV try to imagine you are an employer or recruiter who is going to read it. In managing a recruitment assignment, you are going to have to sift your way through may be 50 or more CVs. You will probably skim read the CVs firstly and then place them into a yes/no/maybe folder. Time is short, impact is essential.

Keep your data analyst CV brief

So, as an applicant, the first thing you need to be aware of is the limited amount of time that will be spent reading your CV. This will generally be less than 30 seconds. There is no point in having a lengthy CV with lots of detail. Keep the CV to a maximum of two pages and about 750 words. Giving yourself this limited platform helps focus the mind so you can think carefully about what to include and not include.

Read the person specification

The recruiter will be assessing CVs on how closely they meet the requirements of the person specification. Read this carefully as this will tell you exactly what criteria and experience they are looking for. The more closely you can align the CV, the better it will perform for you. Tailoring your data analyst CV for specific applications will work much better than using a catch-all generic version.  

ATS Systems

You are no doubt aware of ATS systems that many employers and recruiters use to automatically filter CVs. It is estimated that over 70% of CVs are filtered out by ATS systems before they even get read by human eyes. It is important to incorporate the key words and phrases from a person specification within your data analyst CV. This can be achieved through having a ‘key skills’ section detailing both your technical and soft skills. You should also spread the key words naturally throughout the CV.  

Use facts and figures to demonstrate achievements

It’s not what you do that matters, it’s how well you do it. Simply describing the job responsibilities and duties in your data analyst CV is not going to help the reader understand your impact. In order to create a point of difference you need to demonstrate, through specific examples with facts and figures, how well you have performed in your job. You can also use facts and figures to highlight the scale and scope of projects you’ve worked on, for instance, how many data sets you worked from, how many items of data and the improvements you made in the collection, management and analysis of that data.