How to create a Data Science resume

Welcome back! As a beginner Data Scientist it is extremely important to setup a resume that’s extremely powerful which showcases your skillsets, education and any other projects you maybe working on. Starting off, I would highly recommend having your resume in 1 page, multiple pages seem to give me the least amount of interviews to be honest, but you can add more if needed. Also, this is a barebones resume, all of the formatting and everything is totally up to you, all i’m recommending is the actual text within the document. Also, to give you a quick breakdown of my formatting that I use on my resume / what i’ve seen many of my colleagues do, this is how I would recommend setting up your resume:

Super boring right? but it should get your brain jogging in the right direction. Let’s examine piece by piece.


Literally your name and links to your LinkedIn, personal website or whatever other professional website you have (Github, etc.)


This is a very important segment of your resume, and really the one area that can be moved up or down in your resume. Starting off, in almost every single job i’ve applied to they have highlighted certain education requirements (having a bachelors, masters, certificates, etc.), if you fulfill those requirements then by all means keep this on top, but if you don’t have the exact requirements it may be best to move this down below your work history or personal projects.

Programming languages / Technologies

This is a big one, I literally just put a quick little summary of programming languages / technologies that I know, it may seem dumb but here’s the reasoning: Almost every single website you submit your resume to has a pre built filter, so it’ll pretty much scan your resume for keywords, so if you have every language you know, whether you listed it anywhere else, will at-least increase your chances of getting an interview in my experience. On my resume this little block literally looks like:

Programming languages: R , Python , SQL , Java , C , Javascript , Swift , HTML

Technologies: Tensorflow, Pytorch, Keras, Sci-Kit Learn , Hadoop , Spark , Power BI , Tableau , Excel , etc.

You can rearrange the naming, software maybe a good alternate name to “Technologies” but whatever floats your boat. Also, if you don’t know any languages or software I would highly recommend taking some online courses to build out your skill set.

Work history

This is the holy grail on your resume, this is where you will essentially just drop every single thing that’s relevant to your field that you’ve worked on. Any job, internship, volunteer experience, etc. that you’ve worked on will go here. This is a quick breakdown of how I put a single job on my resume:

Then essentially I copy and paste that same format for every job. Obviously the text will be different, but the format will essentially be the same. If you have no work experience at all, I would essentially replace this specific section with the personal project section we’re going to be building out right after this.

Personal Projects

This section I believe honestly helped me get my first job as a data analyst. First off, this section is pretty much going to hold your personal projects that you’ve done outside of your work, I would recommend doing projects that are relevant but also maybe irrelevant to Data Science, this is what I mean: Instead of just putting a bunch of Machine Learning / data processing projects, maybe build out some front end software projects, or maybe build out a game using Swift or something, or even web development, showing employers that you have a wide skillset could show them that you’re a more valuable candidate. HOWEVER, if you have no work experience as listed above, your best bet is to stay focused on Data Science and only have relevant data science projects: creating Machine Learning models, building out databases, data processing using R or Python, etc. This is what a typical portion like this would look on my resume:

And that’s it! By the end of this you should have a resume that should wow your future employers! Let me know if you have any questions!

Data Scientist / Engineer

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