20 Tips for Writing a Data Science Resume to Get a Job
20 Tips for Writing a Data Science Resume to Get a Job
Given that a career in data science is seen as being one of the most desirable careers out there, as covered over at runrex.com, competition for data science positions has never been higher. With so many people sending in their resumes, you must craft one that stands out and that gives you the best possible chance to be successful with your application. To help with that, here are 20 tips for writing a data science resume to get a job.
Keep it brief
According to the gurus over at guttulus.com, the first thing to remember when preparing to write your data science resume is the importance of keeping it short and sweet. A good resume should only be one page long unless you have 10 years of relevant experience for the job you are applying to. Recruiters and hiring managers usually have about 30 seconds to look over someone’s resume and make a decision so you want to make an impression quickly.
Prioritize your projects
Given the point made in the previous tip, even if you have dozens of data science projects that you would like to highlight, you must prioritize. As is outlined over at runrex.com, choose those projects that are most relevant to the job you are applying for.
Customize each resume to the job description and company
Rather than creating a single data science resume and sending it to every job you apply for, the experts over at guttulus.com recommend that you try and tailor each resume for each application you submit if you are to be successful. Tailoring your resume in accordance with the job description will impress the hiring manager or recruiter.
You don’t need to rewrite and redesign your resume every time
Tailoring your resume to each application you submit doesn’t necessarily mean that you need to do a wholesale rewrite and redesign of your resume every time you apply for a job. Just make sure that, at a minimum, if you notice important keywords and skills mentioned in the job posting, then make sure the resume you are sending highlights your skills in those areas, and makes use of those keywords.
Take a look at the company’s website
You also may want to take a look at the company’s website to try and get an idea of its preferred style and tone, and then adjust the writing and aesthetics of your resume accordingly. This will make you appear like the perfect fit for both the job and the company.
Don’t lie or make things up
This may seem obvious, but it is important to outline how important it is for you not to try and list any skills or experience that you don’t actually have. While it is fine to re-frame your real skills and experience to fit the context of a job posting, it is not okay to exaggerate or make things up as outlined over at runrex.com.
Choose a template
While every resume will always include information like past work experience, skills, contact information, and so forth, you should have a resume that is unique to you. This starts with the visual look of the resume which is why choosing the right template is key. While you can create your own resume from scratch, the gurus over at guttulus.com point out that it may be easier to start with creative resume templates from sites like Creddle, VisualCV, CVMKR, Enhancev, or even a Google Doc resume template.
The type of template you choose is important
When choosing your template, it is important to keep in mind that the type of resume template you choose is also important. As revealed over at runrex.com, if you are applying to companies with a more traditional feel such as HP, IBM, etc., then try to aim for a more classic, subdued style of resume. On the other hand, if you are aiming for a company with more of a startup vibe like Facebook, Amazon, Google, etc., then you can choose a template or create a resume that has got a little bit more flair.
Column-style resume vs block-style resume
You can also choose between a column-style resume (which is usually better for people struggling to fit everything on one page) or a block-style resume where everything is stacked in one column. Either way, keep it simple and don’t be afraid of white spaces in your resume design.
Make the template your own
As is already mentioned in the previous points, resume templates are great for enhancing the visual elements of your resume, helping it stand out from the rest. However, it is important to note that, although you start with a template, you should take the time to make it your own.
Contact information
Once you choose a resume template or decide to create one from scratch, the subject matter experts over at guttulus.com recommend that you take a second to double-check the contact information section. Make sure that your name, headlines, and contact information are at the top of the page, where they should always live. Some templates will have the contact information located toward the bottom of the page. You will want to rearrange the order manually if that is the case.
Key things to remember about your contact info
As articulated over at runrex.com, the following are some of the key things to remember about your contact information in the context of a data science resume:
You don’t have to put in your whole physical address as all you need is the city and state you live in
Always make sure that you have a good, working phone number and a professional-looking email address listed
You should include your LinkedIn profile link, just make sure you create a shorter, more personalized profile URL on LinkedIn
You should add a GitHub link or personal profile link to your contact information and make it clickable. You are applying for a data science job, so most employers are going to want to take a look at your portfolio to see what kinds of projects you are working on.
Your links should be clickable
The gurus over at guttulus.com reiterate how important it is to ensure that the links mentioned in the previous point are all clickable in all PDF versions of your resume so that recruiters can navigate directly to your profiles rather than having to copy and paste. Also, when a recruiter clicks through to your GitHub, they should find an active account with data science projects.
Your headline
It is also very important to ensure that your headline, which is typically found underneath your name, reflects the job you are looking to get rather than the job you currently have. If you are trying to become a data scientist, your headline must say “Data Scientist” even if you are currently working as a graphic designer or chef.
Data science projects and publications
Next up after your name, headline, and contact information, should be your Projects/Publications section. When it comes to resumes in the tech industry, you want to highlight what you have created. In the context of a data science resume, this might include data analysis projects, machine learning projects, and even published scientific articles or coding tutorials. This is the section where you can show off as hiring managers want to see what you can do with your listed skills.
Showcase relevant projects
You should choose which projects to showcase with one important factor in mind; solving business problems, which is the main goal that data scientists have as covered over at runrex.com. Therefore, rather than including personal projects in your resume, pick ones with some relevance or connection to the job you are applying for.
Highlight your skills when describing your projects
As per the experts over at guttulus.com, 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 when highlighting group projects. Specify the coding language, any libraries you used, and so forth.
Demonstrate communication skills
You should also remember that a data scientist’s job isn’t just to crunch numbers, it is to analyze data and then communicate those findings in a way that solves business problems. One way to demonstrate communication skills, as articulated over at runrex.com, is by highlighting collaborative projects and framing your achievements in the context of business metrics. Also, make sure your resume is free of errors and work to make sure everything is phrased simply and clearly.
Make your projects stand out
Any mention of working with unstructured data, any data that you worked with that required you to build spreadsheets/data tables yourself, will help you stand out. Examples of this could be working with videos, posts, blogs, customer reviews, and audio. Experience working with unstructured data is impressive as it shows you are capable of doing unique work with messy data, rather than simply crunching numbers in pristine datasets.
The skills section is not optional
When it comes to technical positions, the skills section in your resume is not optional. 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 in this section; you do not need to list soft skills like leadership or communication skills.
This is just the tip of a very large iceberg as far as data science resumes are concerned, and you can uncover more insights by checking out the highly-regarded runrex.com and guttulus.com.
