Given the growth of data management needs in the corporate industry, the necessity for dedicated experts to enter the market grows by the day. Data science specialists are not easy to come by in terms of hiring them for extended periods of time. According to Finances Online, 69% of employers actively seek job candidates with data science and analytical skills, with 2.72 million estimated job postings for data science to become available by 2020.
There are a clear want and need for data scientists in a wide range of fields and industries, making it easier for specialists in this profession to choose their next career steps. However, the data scientist`s resume you present to your future employer will still be the decisive factor in whether or not you are invited to a subsequent interview. With that in mind, let’s dive into why a properly formatted resume is so pivotal for your data science career development, as well as some of the most vital tips to create your own and land the position you want.
The Benefits of a Well-Crafted Data Scientist`s Resume
Let’s discuss what makes a data science resume so important in the first place before we dive into the minutia of writing one for yourself. According to Tech Jury, 97.2% of organizations are actively investing in Big Data and AI, while at the same time, there were between 11,400 and 19,400 data scientists worldwide in 2015. Compared to the previous figure of demand in a variety of industries and their niches, it’s easy to see the disparity between supply and demand in terms of data scientists.
Creating a well-rounded and focused resume for your future career development will allow you not only to stand out from the crowd but also land the exact position you want instead of hoping for the best. A resume created with care and intent is also likely to paint a very positive, professional image of you to the potential employer, further cementing your chances at employment.
Presenting a company’s HR department with a poorly-written resume that lacks up-to-date information and basic formatting however will have an opposite effect despite any skills or expertise you may have in reality. In that regard, tools such as IsAccurate and Grammarly can prove highly useful in making sure that your resume is written and edited properly. With that said, let’s take a look at several important tips and guidelines to consider when crafting a spotless data scientist`s resume with the intent to land a job position sooner rather than later.
Informative but not Comprehensive
When it comes to writing a job application resume, it’s worth noting that you should keep things simple and straightforward for your employer’s convenience. A job resume should consist of concise, informative data in regards to your past experiences, skillset, and education, rather than comprehensive, multi-paragraph writing about who you are and why you’re applying. This information can (and should) find its place in the motivational letter which can accompany your resume as a bonus and allow the employer to get a better idea of who you are as a person outside of your data scientist profile.
That being said, make sure that you approach your resume writing with the intent to write short, direct information about what you did when you did it, and what the outcomes of those actions were – no more, no less. You can refer to tools such as Best Essay Education and Hemingway if you are stuck in the editing phase of your resume and don’t know how to make it more readable or skimming-friendly. This will be seen as a positive by your future employers’ given that it’s difficult to shortly sum up one’s thoughts in a concise manner, something which will be required of you by default in the corporate paperwork if you are hired.
Personal Certification & Skillset
Typically, resumes should contain professional experiences and education before jumping into the skills and certification section. However, given the specific nature of data science and the versatility of your skillset, you should open with the personal certification and skillsets outlined for your employers’ convenience.
Whether you specialize in coding languages such as Python, SQL, and C or lean toward conversational AI integration, data analysis, visualization, and project management, these skills should all be listed alongside professional certificates, seminars, and conferences you’ve attended. As we’ve previously mentioned, there is no need to elaborate on any of the skills you’ve listed in this section in the resume itself – the chance to do so will be presented to you in the interview itself. This will quickly paint a picture of what type of data scientist you are and whether or not your profile fits into the requirements outlined by the company’s HR.
List your Projects & Employments
Once your skills and certification are clearly outlined, you can proceed to the professional experiences, projects, and employment you’ve been engaged with prior to this moment. Make sure to list your experiences from the most recent contract or project and move backward to the most distant ones.
Each item should be followed by bulleted accomplishments or KPIs which relate to that project to illustrate what objective outcomes you’ve attained during your employment. If editing and paraphrasing your accomplishments becomes challenging, you can refer to writing tools such as Supreme Dissertation and WritingJudge for your convenience. This will allow the employer to scan through your accomplishments and surmise how you’ve grown as an individual and data science professional.
Outline your Education
While formal academia won’t impact your data science employment chances by a large margin, having a college education and a degree related to IT will certainly make a difference. This section is especially important if you are a fresh graduate or have just finished your first internship or volunteering in a data science enterprise or position.
As with previous sections, your education should be outlined from the most recent experience and go back in time. You can add smaller details such as your average graduation score, the thesis you’ve worked on, as well as any awards or accomplishments you’ve achieved during your education (in several words only). Keep the section clean, informative and focused on your growth in order to achieve the best effect in regards to landing employment.
Contact Info Matters
Many assume that the contact information section is a given in job resumes. While your contact information will find its way into the data scientist`s resume in one form or another, this section should be treated with equal care and attention for detail as any other. With that said your contact info should always be up-to-date and contain communication channels which you often visit to check for new messages.
Channels such as your email address, LinkedIn profile and other social media handles (depending on the company you apply for) should find their way into the contact information. While you can add your phone number (mobile, not landline), you should omit your home address if possible – there is no need for every employer you contact to know where you live by default. Check your contact info every time you are about to send the resume to a new data science job application to make sure that it’s still valid and free of errors.
Lastly, once your resume is formatted and ready for future data scientist job applications, you should keep the recipient and their expectations in mind. Every company will expect different things from their candidates and future employees, whether that is a style of formatting, knowledge of the company’s history or something similar.
Make sure to research each company you plan to reach out to in regards to their job opening prior to doing so. This will allow you to find out more about your potential employer, their business culture as well as whether or not it is a good fit for you as an individual. Adjust your resume accordingly if you find out interesting information about the company and the way they process job candidates to maximize your odds of landing an interview and getting hired shortly thereafter.
When all is said and done, applying for data science positions is very similar to other job applications in fields such as IT, programming or data management. Put effort into crafting a resume that will represent you as a person and a professional in relation to your aspirations to work as a data scientist.
While not every company will welcome your specific background and profile, those that do will be very willing to hire you for the foreseeable future. Start your data science journey today and write a resume that you can be proud of and it will undoubtedly kick-start your career on the right foot.