Writing a brief summary of your Data Science experiences may sound like a breeze, but you’ll only feel the struggle when you start working on it. However, fret not! Here are some tips on how to write a clear and concise resume that will catch your recruiter’s eye.
Keep Data Science resumes brief
A rule of thumb when it comes to writing a resume is to keep it short. Always bear in mind that your recruiters receives tons of resumes every day and they usually have about 30 seconds to look over someone’s resume and make a decision. Therefore, a good resume should only be one page long. Even if you have tons of experience and dozens of data science projects you’d like to highlight, you need to prioritise. You want to boil down your experience to the most relevant points so it is easy to scan.
Showcase relevant Data Science projects
Data scientists have one goal and that is to solve business problems. Thus, showcase projects that demonstrates this important factor. Additionally, you should pick projects with some relevance to the job you’re applying for. These projects should demonstrate your technical skills, but ideally, also demonstrate how your technical skills are applicable to solving real business problems. You definitely want at least one project or publication on your resume, but if you have space for more, add as many as you can neatly fit.
Highlight your skills
When you describe each project, be as specific as possible about the skills, tools, and technologies you used, how you created the project, and what your individual contribution was if you’re highlighting group projects. Specify the coding language, any libraries you used, etc. Don’t worry if it feels as if you’re repeating the same skills you plan to list in your skills section. In fact, the more times you can add those key tools, technologies, and skills in your resume, the better. Recruiters and hiring managers often use simple keyword searches to scan resumes, and you want your relevant skills highlighted in as many spots as possible when they search your resume.
Your most recent work experience should be listed on top, with the preceding jobs below that in chronological order. However there are a few things to note for this section. Firstly, if you’re listing jobs that go back further than 5 years, you might want to only list relevant work experiences. Secondly, make sure your description primarily consists of your accomplishments rather than duties. Your potential employers want to see what you actually did, not just what you were supposed to do. Another good advice would be to frame your data science accomplishments in the context of business metrics to demonstrate that you understand the big picture and know how to translate your analysis results into real business outcomes.
Although it is great to have a degree, you probably don’t want to highlight that first on your resume unless you’re a graduating student looking for their first job in a relevant field. Under this section, you should only list your tertiary certifications (i.e. Nitec, diploma, graduate diploma or degree). If your degree is not relevant to the job you’re applying for, you should still list it. Some positions simply require a degree in any field, so you want to ensure you’re in the running for these positions. However, if you don’t have a degree, don’t worry too much about it! Simply leave the Education section completely out of your resume as it may send a red flag for recruiters and hiring managers. Finally, don’t list “micro-degrees,” online training certificates, or other professional training here. Many data scientists have this sort of training, and it’s fine to include these certificates on a data science resume, but they should instead be listed under the Skills and Certificates sections.
The skills section is not optional
For technical positions, this is a necessity! Recruiters and hiring managers will most likely do a keyword search as a first step in viewing your resume, so you want to make sure key terms like “Python” or “Machine learning” are highlighted. Only list technical skills or tools here. One trick to note is that recruiters looks at your skills is by assuming that the skills you list first are your strongest skills, and the skills you list last are your weakest. For that reason, list your strongest and most relevant skills first, and leave skills where you’re less comfortable or that are less likely to be relevant to the position for later in your list.
Once you’re finished adding all of the relevant content to your resume, the last major thing you’ve got to do is a spell check. Recruiters go through hundreds or even thousands of applications, so don’t give them the opportunity to trash your resume. It may be hard to catch them yourself, so have a couple of trusted friends take a look at your resume! They may be able to catch on small errors that you missed.