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5 Simple Tips for a Perfect Data Science CV

Having a compelling data science CV will help you get your dream job. There is no doubt about that.

However, writing a CV is one of the worst parts of job hunting. How is it that something so crucial for getting your dream job is never really taught to you? 

In particular, if you are coming from a STEM background writing a CV is never discussed. I remember frantically googling CV writing tips when I was about to finish University to try to get my first job.

Luckily I was able to get into a Graduate scheme where I remained happy for three years. However, I realized that working as a research chemist was not for me, so I decided it was time to move on.

Unfortunately, that also meant updating my CV.

I worked hard at it, spent a long time updating my experience. Then I shared it with a friend.


She pretty much ripped it up and then spent the next 3 hours restructuring and re-writing everything. My CV efforts had been terrible.

I was lucky to have my more experienced friend to help me re-write the CV. Since then, I have become much better at CV writing and evaluating other people’s CVs.

However, not everyone has that kind of help when they are getting started. To help you here are my tips for crafting the perfect data science CV.

5 Tips for crafting the Ideal Data Science CV

Here are 5 of my top tips for crafting your CV that will help it to stand out:

  1. Use keywords: Check the job description and make sure you use the same terms in your CV
  2. Quantify everything: For everything you say you have achieved make sure you back it up with a data point
  3. Pay attention to structure: Make sure your CV is laid out well and please no spelling mistakes!
  4. Keep it short: Use short sentences and keep everything to the point. Don’t go over two pages
  5. Make yourself easy to find: Make sure you have your contact details at the top of the CV. This layout makes it is easy for recruiters to get in touch about roles.

Crafting an excellent data science CV doesn’t have to be so hard. However, if you want to impress, it might be worth calling in some help.

data science CV

How to structure the perfect CV – if you need more help.

Need some more help? Well, you are in luck because my friend Kristen (datamovesher) has created the perfect course to help you craft your data science CV.

Delivered over nine lessons, you will learn everything about writing a data science CV.

I particularly enjoyed the section on LinkedIn. Kristen is a top 8 on LinkedIn voices in Data Science and Analytics, so you know she knows her shit.

I also loved the bit on how to beat the sorting algorithms to make sure your CV gets seen. Getting past the algorithms can be tricky. My partner works in recruitment, so I know just how ruthless those algorithms are!

get cv help

What if this is your first data science role?

This course can help you write a data science CV. The course will teach you even if you have never had a data science position before. You will learn how to use your skills and background to prove why you are perfect for the job.

The way that you can take advantage of your skills and backgrounds is something I am especially passionate about. We need more diverse voices in data science. Making sure your CV stands out is a great way to get started.

Everything is covered, from how to structure your CV through to how to quantify all of your results. This course has everything you need.

You can learn more about it and sign up through Kristen’s website (Link).

Advertising Disclosure: I am a proud affiliate and may be compensated in exchange for clicking on the links posted on this website. I only advertise for course I have found valuable and think will help you too. 

Ready to get serious about a career in data science

Whether your a self-taught programmer or have a Ph.D. in data science, you need to have a compelling CV.

Take your data science CV seriously.

Once you have finished crafting the perfect resume, then it is time to look at your brand and network. Here is a link to another article on getting ahead with your data science career

Go forth and prosper! Data science needs you!


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