7 tips to help you construct the perfect Data Science CV

24th April 2019


CV builderWriting a Data Science CV isn’t such an enjoyable task but just as surgeries are important to doctors, a thorough CV is important to the career of every Data Scientist.

It’s the first step to making a good first impression, these 7 perfect tips that will help your CV standout:

Be brief

Except you have over 10 years of experience in data science, consider making your CV just a page long. Recruiters and hiring managers receive lots of CV’s daily and only have a few to scan through each. To make certain your CV isn’t tossed aside, make your CV easily accessible by boiling your experience down to important points.

Pick a CV template

Your CV has to be unique and its visual appearance must be appealing. It’s either you create it from scratch or use CV templates form various sites. Google Doc also has some cool templates that could work for you.

Regardless of the template you choose, it must be professional and apply to the company’s style.

Mention your educational background

Entry-level candidates may not have a lot of experiences to list. A solid educational background in a mathematical subject becomes more important here. A BSc and relevant course works are guaranteed to grab the attention of any recruiter.

For individuals with years of valuable experience, mentioning a Ph.D. or at least, an MSc is definitely a plus.

Focus on your programming skills and experience in research.

Every Data Scientist must have programming skills. Using these languages is quite necessary for your CV.

It is important to avoid using too many languages. Three to four languages make your CV look more attractive. Python, Java, R, C#, etc. can be mentioned (along with your proficiency with the languages) to double your chances.

Every recruiter needs practicality and stating the university you bagged your degrees from can never be enough. They’re mostly interested in the details of your research and how successful it turned out.

You don’t have to attach your thesis to your CV, but summarizing the key aspects of your research in one paragraph puts you in a vantage position. It is also a great way to express your written communication skills!

Demonstrate your knowledge by citing specific technologies in the right context

Different job fields have different languages and just like a lawyer throws around court-related words, a Data Scientist should too.

Your CV should not just be a list of degrees and objectives, it has to reflect your expertise and make your claims believable.

Express your technical depth

Although this may not be applicable to entry-level candidates, it’s quite important for senior level Data Scientists.

Mention external accreditations (if you have any) such as a chartered status, i.e. Chartered Scientist or Chartered Mathematician is a great way to demonstrate your capabilities.

However, keep in mind that mentioning a variety of problems you’ve worked on will be much more acknowledged. Evidence of technical depth and how you solved a problem, either with a team or as an individual, will make perfect CV support.

Tweak your CV for specific Data Science jobs

While it’s good to create one single CV for every Data Science job you apply for, tweaking it in accordance with specific job descriptions is great.

It sure requires extra work, but adding these little details can make a good impression on the hiring manager.

You don’t have to re-work the whole CV! It’s practically for the same job, right? But to be on a safer side, take a close look at the job posting and try to take note of important skills they need or keywords that you can add to your CV. The company’s website is the next place to visit before you send in your CV and if you want to make your CV look good, focus on your impact.

What impact does your expertise have on the real world?

Give the hiring manager concrete reasons why they should hire you and this might sound not worthy of mention, but completely avoid including any skills you have no knowledge about.

Read also: Can a Data Scientist do the work of a Data Engineer?

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Oluwatobi Ogunrinde

A passionate writer hoping to educate people with her work. Oluwatobi enjoys writing about entrepreneurship and work culture. When not writing, you will find her reading about international politics.

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