How to write a data science CV that gets you hired

By Indeed Editorial Team

Updated 17 June 2022

Published 3 January 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.

Writing a data science CV can be a challenge, but having a strong CV that is both structurally and aesthetically sound is important for your career. It can help you gain access to more desirable job interviews and increase your earning potential. Knowing some of the best practices to use when crafting your CV can help you produce one that is more effective. In this article, we explain how to write and proofread your CV that increases your chances of getting hired.

How to write a data science CV

Writing a data science CV may seem like a tough task at first, but it is a necessary step to advance towards a career as a data scientist. Before they invite you to an interview, your CV has to stand out from the potentially large number of CVs already submitted. A CV summarises your professional skills, experience, qualifications and education. It is important that this account is concise and brief, allowing the employer to see quickly if you are right for the job. Below are some tips that can help you write a sharp and focused CV that allows recruiters to see your professional skill set.

Keep it brief

Think of your data scientist CV as a tightly packed parcel, something tidy and of a suitable size to send to the recruiting department. As recruiters read a vast amount of CVs per day, they spend around 6 to 8 seconds deciding if you are suitable for the role. As a result, the optimum length for a CV is about one page. It is essential to filter your relevant experience to one or two examples and include your highest qualification.

Related: CV format guide: examples and tips

Select a professional template

Your CV holds the core information of past experience and qualifications, but it's advisable to choose a professional layout to make your CV more noticeable. Some websites provide you with pre-existing templates, alternatively you can use YouTube tutorials to guide you in creating a completely fresh look for your CV. It is also recommended to do some research into the company via their website. If the organisation favours bold graphics and artistic flair, then adjust your CV accordingly. Whatever aesthetic you choose, remember to keep it brief and simple. Your CV needs to be distinct, but also professional.

Tailor your CV to the company

It is not advisable to write a completely new CV for each role you apply for, but merely to tweak your primary CV. Keeping the job description and ideal employee checklist open while you edit each CV is a quick way to impress the recruiters. It implies you have thoroughly read the job posting and are aware of the responsibilities and requirements of the role. In addition to this, researching the company, especially the style of writing on the website, gives you a good idea of the company's ethos and the style of communication they prefer.

Related: Why is a CV important? (Everything you need to know)

Check your contact information

First, it's highly important you include your current address, email address and phone number. Although this may sound simple, it is important to remember if you are editing an old CV, as this is easy to overlook. In terms of format, we usually find the contact information at the top of the page, as it is the most relevant for the next phase. Alternatively, place it at the bottom, but it is advisable to include it in bold letters, as it can be easier to find. Below are some key points specifically for data science CVs:

  • Include a shorthand version of your address. Use your city and county. If you are willing to relocate, it may be advisable to omit your current location.

  • Use a working business phone number or be ready to answer professional calls. Ensure your phone number is up to date and not an old contact number. Although not always practical, having a separate phone number for business calls might be a good idea so you're ready for calls.

  • Add a link to your portfolio. These are essential for data science roles, so add them via an online portfolio platform. The employer needs to see your past projects and that you are working regularly to practise your trade.

  • Include a relevant career headline. Ensure that the headline beneath your name best describes the job you are searching for, i.e., data scientist not management consultant. This gives you more legitimacy when applying for data science roles.

Feature the most relevant projects

As data science roles are creation-oriented, it's a good idea to create a list of publications following the initial information on your CV. This is like a mini version of your portfolio where you can impress employers with your past achievements. Ensure the projects you showcase are relevant to the role you are applying for, in the same way as your skill set. Also, show through these projects where you have solved problems relating to important business issues. It's desirable to include at least one project you have worked on in the last six months or sooner.

Related: What is a visual CV? (Plus tools to create one)

Include technical and interpersonal skills

Technical skills are relevant to data science roles and have an essential place when writing your CV. Ensure you include the tools and technologies you used. It is common for recruiters to use keyword search tools when scanning CVs, so matching the relevant technologies from the job description is the best way to ensure recruiters spot your CV. Alongside technical skills, interpersonal skills are equally important within the workplace. Communication is an essential element of your skill set. An effective way to show off your communication skills is to ensure your CV is well-written and direct. Other ways to demonstrate communication skills are:

  • Collaborative projects: This shows your ability to work with other people and create projects as part of a team.

  • Use keywords closely related to communication skills: These can include phrases such as, 'Listened to managers' feedback to augment my skills as a data scientist.'

  • Using business metrics: This shows that you are a capable statistician and can connect this to the mechanics of business.

Include past experience

Experience is the singular most important aspect of your CV for a lot of employers, so it's essential you include the most relevant and impressive experience on your CV. Your past work experience is usually in chronological order on your CV. It's always best to put your most recent at the top. Also, remember to include all experience within the last five years. This helps employers build an idea of how capable you are. Always account for gaps of six months or longer on your CV. These are noticeable to employers, so prepare yourself to explain if they invite you to interview.

Related: The ultimate guide to CV basics (with example)

Formatting your experience section

Bullet points are infinitely useful for listing your achievements in past roles. Remember to keep these brief and to focus on achievements rather than daily tasks. In addition, if you use bullet points for one role, ensure you do it for all of them. It's a good idea to keep your CV looking consistent in this section. Here are three examples of items to always include in your previous job descriptions:

  • Full title of job role

  • Name of the company

  • Period of time you worked for the company

Both your experience and project sections are to show your abilities, so ensure this section is well rounded and polished before you submit your CV.

Proofreading your CV

Finally, before sending your CV to any data science employer, it is ideal to use a spelling and grammar checker. These kinds of mistakes can be glaring for employers, so it's important to use a professional spell-check tool. Whichever way you choose to finalise your CV, remember the role of a data scientist requires deep analytical and communication skills. Be sure to reflect these in your CV to maximise your future job opportunities.

Peer review

To be additionally thorough and ensure that your CV is as good as you can possibly make it, have a friend or professional acquaintance read your CV. This can help you improve the quality of your CV, as they might see something that you have missed. If your peer identifies any errors in the reviewing process, you can address them accordingly before you submit them to potential employers.

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