How to write an effective Data Scientist resume (with a real example)

How to write an effective Data Scientist resume (with a real example) Data Science has become one of the fastest-growing fields in recent years. It has also been mentioned as one of the world’s best jobs across several industries and has a very lucrative career trajectory â€" the average salary for a data scientist in the US in 2016 was over $100,000. But standing out and getting a job in this competitive field is a real challenge.Ultimately, a great resume is one of the most effective ways to get noticed. As we’ve learned from Pavel’s story, an effective data scientist resume can have you on the track to a fulfilling and exciting career. Steps for Writing a Data Scientist ResumeTo write a successful data scientist resume, you can make use of these steps that we’ve distilled from Pavel’s approach to getting hired at Booking.com.1. Research opportunities in the fieldBefore putting your resume together, you need to see what vacancies are out there. Data science is not limited to one field and it can be fruitful to specialize in one sector or an other. Personal networks are one of the most effective ways to find opportunities. Pavel benefited from being referred to the position by a friend. You can start by checking LinkedIn connections or asking around your networks.2.  Analyze the job descriptionUnderstanding the job description will allow you to tailor your resume to the specific requirements of that vacancy. “I customized the [resume] in a way that it addresses everything that the requirements in the position description said.” Pavel used this strategy when assessing the vacancy with Booking. The better you understand what the company is looking for the better you can tailor your resume perfectly.3. Find resources on the topic While data science is a new area, there are resources out there that give some insight into the types of things recruiters are looking for. One of the best sources of information for this are books on interview questions for data scientists (which are actually a thing, look them up). Glassdoor is also perfect for finding past interview questions. Pavel credits this kind of research into past interview questions as being crucial “I bought those books which were expensive but I’m very happy I did that now.”Understanding the questions that you might be asked in an interview allows you to specify experience in your resume. If you know you’ll be asked about coding, make sure that’s included in the resume; even if its not heavily featured in the job description. 4. Build your resume with a flexible platform Often, resumes are split into two categories. As Pavel puts it,“There’s two components: aesthetic, the more beautiful the piece of paper. And the second is the content. What I really appreciate is that Enhancv supports both components”. When you create your resume, you want to make sure it’s relevant to the vacancy (as covered in step 2) but it needs to catch the recruiter’s attention. Melding both of those together puts your best foot forward and gives you the best chance at landing an interview. 5. Put your resume through a review You’re not always going to catch mistakes in your resume. It’s also very difficult to predict how your resume reads from another person’s perspective. Having friends look over your resume â€" or even other professionals in your area â€" is the last thing you should do before sending it out in an application. With Enhancv, you can easily refer your resume to others using our built-in referral link. This way, friends, family, and colleagues can leave comments suggesting edits where necessary.Writing Your Data Scientist Resume These real resume examples have shown that a great data science resume accomplish three things: catches the attention of the recruiter, answers the questions of the job description and shows your personality. All three are doable using a clean, pleasing design. Like Pavel, you can try our Enhancv builder to create a resume that ticks all the boxes for aesthetics and content.