The 6 Best Ways for Student Resumes to get noticed by Data Science Employers


The 6 Best Ways for Student Resumes to get noticed by Data Science Employers

I am currently a Master's student in Statistics, and am interested in and trying to get into the Data Science job market. I am wondering what would be the best means of showcasing my skills.


If you're a student looking to break in to Data Science, you're unlikely to have a lot of relevant work experience, so how can you get noticed by potential employers? What can you start doing now that will help your resume (and you!) when it comes to the job search? There are several ways to go about this...


  1. Independent Projects. The best projects are ones you're interested in solving - where the problem comes from you. The more specific the task/question you can set yourself, the better, as this will help define the data and analysis required. If you can develop a portfolio of 5-10 independent projects using different techniques and languages that you know, you'll have great material to reference on your resume (and be able to tailor what you show to each job, depending on its requirements).

  2. Company Specific Projects. Completing a project with direct relevance to the job you're applying for is probably the strongest way to signal competence and commitment. Imagine how impacful your resume would be if you'd proactively come up with a topic, found data, and run some analysis on an issue you think the company might be facing? This is a great way to get noticed by a Hiring Manager!

  3. Networking at Meetups. Armed with an interesting project or two under your belt, it is well worth attending local data-related meetups. There are often people there who are hiring, and you'll have something tangible to talk about. Building those relationships now will help when it comes to submitting your resume.

  4. GitHub Write-Ups. For projects that you do, it is well worth putting together a simple write-up and your code on GitHub, that you can link to from your resume. Creating a readme.md for the projects is often the easiest - this template is a good example. You can also do this for coursework projects that you've completed in your studies.

  5. Find Ways to Present your Time in Academia as Job Experience. Academia cares about publications. Data Science Hiring Manager's care about relevant skillset and experience. As such, look for ways to make your studies come across as experience. For example, make sure any research positions you're listing include not just a description of what you were doing but how you were doing it (techniques, programming languages, software etc). Try at all times to explain the relevance of the research to the job.

  6. Build some Domain Expertise. While by no means critical to landing your first job out of school, learning some domain (i.e., industry specific) content can help set you apart. It can be especially handy when it comes to writing a stand-out cover letter. If you know some of the main issues facing the industry, it is much easier to be very specific on the types of projects you're excited about tackling, and why you think you can add value.


How to take action now?

Pick your favorite project from your coursework to date. If you enjoyed doing it, you'll likely be excited to write and talk about it! Pull up the example Readme.md template and put together a write-up you can post to your GitHub profile (and if you don't have a GitHub profile yet, that should be step zero!) :)


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