There are a lot of things to consider when writing your CV. Even simple things like what font to use, whether you should use bold or italics and other features are important to help your CV stand out amongst the crowd.
Small details make the difference in the eyes of hiring managers, so creating that well-designed standout resumé could allow you to leapfrog your competitors and land you that all-important interview. However, creating a functional Data Science CV is a little more complicated than choosing a simple font.
The first thing to consider when submitting your CV is to know your audience. If you’re applying directly on a website for a position within a large or medium company, it’s very likely that your resumé will be subject to an Application Tracking System (ATS).
Tailoring your CV to get past ATS.
There are a few things to remember when dealing with an ATS:
Your CV will not be seen by a human if it fails to get past the ATS. So even if you are the most talented data scientist in the world, it won’t matter.
Don’t be fancy. Keep it simple by using standard fonts such as Arial or Calibri. Excessive formatting or decorative elements might present an unreadable mess to the ATS.
Make it keyword-rich. The ATS is looking for keywords specific to the job so you should always tailor your CV using words from the job description.
Target the right keywords. If you’re applying for a management position, you’re going to be scored on keywords that are relevant to qualities that are expected of a manager. Once again, review your job spec to find suitable keywords.
Keep it simple. A simple CV that hits all those keywords is far more likely to get past ATS.
However, if you are emailing a recruiter or HR personnel directly, then you will be able to get more creative with your CV.
Here are our top tips for your Data Science CV.
First impressions: Write a great summary
Be convincing here! You are selling yourself, so try not to be too factual and choose what language you use carefully. When writing your summary, imagine you are a marketing expert and you are advertising yourself. Here is a good example:
Use words like 'specialist' 'boost' and 'invest' which are powerful words and can hold sway over the reader. This section tends to be a more tricky part of the CV, so think it through thoroughly.
After touching on this in your summary, it's time to get into some real detail.
The experience section should be the focus of your resumé. Remember to keep it recent and relevant. You should definitely list all of your work experience but don't go into detail on any that are older than five years. It is most likely irrelevant to high-end data science projects in 2022.
Make sure to include your job title, the company and the period of time you held the position.
If one of your past roles has more relevancy to the position you are applying for, then be sure to highlight that above all else. Remember to talk about how your work benefited the company rather than 'my tasks were x, y and z.'
We find it is best to use bullet points in this section. Try to include information like this:
Obviously, if you are a recent graduate then education will be the highlight of your CV. Remember to list post-secondary degrees only! If you are a graduate, you can definitely go into greater detail in this section.
Like with your experience be sure to list all of your degrees, but only go into detail with your most relevant accomplishments.
As for your GPA, this is an optional data point. However, if your GPA was 3.8 or above, it is perfectly fine to brag a little bit about yourself.
This section is pretty straight forward just remember the following points:
Highlight your strongest relevant skills and list only the programming languages you feel most comfortable with. You can list relevant soft skills if you want, but the focus should always be on your technical skill set.
Certifications - You can list any 'micro-degrees' in this section e.g. online courses, professional training etc. Again keep it relevant and recent.
Projects - One important factor to remember here is to focus on how your project solved a business problem. Hiring managers don't care how difficult the problem was or how cool the solution is. Keep that in mind when including projects on your CV.
Publications - Highlighting any articles you have written showcases your passion for data science. With Data Science roles, you will need you to interact with a variety of audiences, so it’s good to show you can explain ideas in a clear and efficient manner.
Hobbies and Interests - Only talk about your hobbies if they convey something about you. Don't say ' I like travel '. Say, I have travelled to x many countries and am fluent in x.
A CV is never a one size fits all, so use these particular sections as you see fit.
Bonus: Crafting the perfect cover letter
Our advice on this subject is simple: Less is more. I find that the majority of my candidates are much better at writing code than they are cover letters anyway. Another thing which you should try to avoid is following that 'typical cover letter format' that you see plastered all over the internet. It will give the reader the impression that you are unimaginative and tired.
Obvious copy and paste cover letters will just give the impression that you are not that interested in the position. You see, there are a lot of pitfalls to consider when writing your cover letter.
In our experience, most cover letters that we see are actually detrimental to an applicants success. Keep it simple with something like this:
Dear Mr. Hiring Manager
I would like to apply to the position of Head of Data Science. My CV with detailed job experience is attached. The job description sounds really interesting to me as both fun and challenging. While, [Insert company name] seems like the perfect place for me to learn and further my career! Whenever you are free, I would love to sit down and have a chat about the projects I might be working on and the tools that are being used.
If you have any questions for me about my CV or otherwise you can reach me by email or directly by phone.
Thank you for your time,
These kind of cover letters are perfect when applying to a company in which you have no contacts such as Linkedin or Glassdoor. Please do not use templates that you found on the first page of Google, you will end up sounding like a robot and companies don't hire robots (yet!).
In summary, there is no one standard CV or cover letter to use when applying for your next data science role. If you follow these top tips, then you will start edging closer to landing that dream job.