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Data Scientist CV : 5 things that should not be included !

Margalith

Margalith

3 min

Competition is increasingly fierce between aspiring Data Scientists who have recently graduated. Discover 5 things not to put on your CV so as to gain an advantage over other candidates …

These last few years, the profession of Data Scientist has been considered one of the best professions through all sectors. Very high remuneration, attractive employment opportunities, extremely high demand …

The strengths of this profession are numerous. However, in the face of these advantages, competition is growing among young data scientists who have just graduated.

To find the job of your dreams, it has therefore become essential to take care of your CV. Through this article, discover 5 things not to put there … 

Avoid a too vague presentation

It is important for aspiring Data Scientists to avoid presenting a resume that is too vague. By listing only experiences and goals that are relevant to the data scientist job, you will better capture the recruiter’s attention and gain an advantage over other candidates.

This also applies to the lists of your skills, diplomas or training. For example, you can start your CV by specifying whether you are a junior, senior or if you just graduated as a  Data Scientist.

Next, present your goals and what you think you can bring to the company. To put it simply, it is best to personalise your resume to the position you are applying for.

Do not mention skills or training without an internet link

To be credible, it is better if a Data Scientist’s CV is presented as an online document rather than on a sheet of paper. This format gives you the opportunity to add web links to pages in order to  highlight or authenticate your skills, training and past projects.

For example, you can place links to LinkedIn, Kaggle, GitHub, or even the DataScientest website if you have taken our training. This way, employers will have a better overview of what you have accomplished so far.

Focus on results rather than method

To be successful, a Data Scientist must bring concrete and actionable results to the company through data analysis. Therefore, on your CV, there is no need to focus on the methods and algorithms that you deployed during your previous projects.

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Favour a clear and concise CV

Do not cite irrelevant projects

To prevent your CV from blurring in the eyes of the employer, it is best not to include projects or experiences that are not related to the position you are applying for. Highlight your original projects and directly linked to the position in question.

You need to try to convince the employer that you can approach a problem in an unusual way, or that you can tackle problems from various areas. If you have confidence and versatility, you will be able to retain the recruiter’s interest. So prioritise projects that reflect your skills, knowledge and problem-solving abilities.

No need to present professional experiences unrelated to the position

Just like projects, previous professional experiences that you cite in your CV must be directly relevant to the position sought. In general, unrelated information may overshadow information that is important to employers and cause them to lose interest in you.

To avoid this situation, it’s best not to bring up your work experiences unrelated to data science. The only exception is for experiments performed at a prestigious company with a reputation for using data science. 

To conclude, favour a clear, uncluttered CV, focused on results and in an interactive form. You will therefore maximise your chances of landing a Data Job. If you enjoyed this article, check out the common mistakes to avoid when learning Python.