Tips And Templates For A Data Scientist Resume
Creating a resume for jobs is the most crucial step for employment. And when it comes to data science jobs, the chances of a resume going haywire is quite more as there are a lot of skills and credentials that may need to go into the resume. There may also be confusion about what to include and what not to include, and how detailed should the resume be. Writing a concise and reasonable resume that resonates with hiring managers might be a tough task. With this article, we bring a few hints about how you could go about writing a resume for data science roles. We have divided the article into two sections — first is tips on what a data science resume should include and second on the resume templates that may work well to include the details. 10 Tips To Write Your Data Science Resume 1. Customise your resume according to the job role: This is the most important and significant tip while designing your resume. Before beginning with filling the info do thorough research about the company, the job role that you are applying for, tweaking the skills and experience, the company’s style and tone of writing. Customising these details can win you over others. It does not mean rewriting and redesigning the resume every time you apply for the job but making it recruiter-friendly. 2. Keep it brief and to the point: Keeping the resume short and brief may work wonders for you. Whether you are a fresher or a professional with a few years of experience, most recruiters prefer looking for a brief and to the point resume. It works best if your resume is not more than two pages long or maybe three pages if you have more than 10 years of experience. 3. Organising and prioritising it to catch maximum attention: Since we need to keep it brief, the need to highlight and prioritise the resume comes into the picture. It is advisable to keep the most significant data science projects or work experience on the top to get maximum exposure. Most recruiters read resumes from upper-left to bottom right and it should, therefore, be designed accordingly. 4. Adding a summary of your career so far: The summary should be few impactful lines that include information such as why you want to be a data scientist, what are some of the skills you pose that deem fit for the role, what have been work-related result-driven accomplishments that you have achieved in your previous jobs. It should be written in a way that tells a short story about your career so far while conveying your long term goals. 5. Highlighting technical skills, certifications and accomplishments: It is the most crucial information for any data science job roles. It should include in-depth details about tools, programming languages and other accomplishments that you pose. To make maximum impact, it is advisable to have studied and learnt the most required tools and technologies that data science job roles demand. It will help you be on the top of the game compared to other candidates. Not just listing the tools but briefing about how you made use of those skills in your past job should also be added. 6. Adding project work, research work, publications: Adding project work and publications that you have accomplished in your career is most advised. Adding LinkedIn profile or GitHub profile links that cover these details will help employers have a better understanding of the skills and capabilities that you pose. 7. Adding soft skills: Soft skills are as important as technical skills when it comes to making a career in data science. Since data science job roles include engaging in communication with other teams in an organization. Therefore the ability to communicate complex information into simpler words effectively is a quality that most organisations look for. Some of the soft skills that you can add in the resume are critical thinking, problem-solving, open to learning new skills, storytelling, and more. 8. Work experience: It gives an insight into the professional experience of a candidate while highlighting the kind of job roles you have handled in the past. It is always advised to put up the latest work experience on the top with the preceding job in sequential order. Any gaps in the career should also be mentioned in the resume to avoid any confusion and doubts in the recruiter’s mind as they sift through your resume. You may skip adding detailed information about the work experience that isn’t relevant to the data science position and may just add the organisation name, your job title, and the dates worked. 9. Adding a note on your educational background: Adding a column about education is a good idea while preparing a resume for data science roles. It will be an indicator of all the hard work you have put up behind the scenes to reach where you are today. Some of the information you can add are university and major, GPA and final marks, awards you have received or societies you were a part of. It is especially important for entry-level data scientists. 10. Spell check grammar check: While most candidates may skip this part, it is crucial that the resume has been run through a grammar and spelling check. Once the resume is complete, it should be run through spell check websites such as Grammarly. There are a lot of other free websites available that do grammar and spell checks. Having grammatical or sleeping blunders in your resume may put off your work against recruiters despite having significant accomplishments. 5 Templates That You Can Make Use Of While Creating Data Science Resume Resume is about a lot of information and it is important to organise and prioritize information to get the eyes of the recruiters. Essentially a resume can be outlined as below: Name with details such as Phone number, Address, EmailSummaryExperience and responsibilities with details such as Position, Company, Address, DatesSkills & Knowledge such as Languages, Technical Skills, Soft SkillsPublicationsEducation & Certificates It is important to pick a template that displays all of this information while making up for a unique layout. There are many job portals such as Indeed and Monster that help candidates with resume samples. Some other websites with resume templates are Canva, VisualCV, Google Doc resume format, SlashCV among others. Keeping in mind that the maximum time that a hiring manager spends on a CV is not more than 30 seconds, it is important to choose a template that complements your content and is pleasing to the eyes but not too flashy. Some of the other details to keep in mind are avoid long text, use bullet points, use professional fonts, add colours but do not overdo it, and most importantly keep it short. Some of the formats you could pick from are single column, double column, condensed, modern and others. Download this template here. Get a 7 day free trial of this template here. Explore this sample here. Source: Springboard Access this resume template here.
Creating a resume for jobs is the most crucial step for employment. And when it comes to data science jobs, the chances of a resume going haywire is quite more as there are a lot of skills and credentials that may need to go into the resume. There may also be confusion about what to […]
We have divided the article into two sections — first is tips on what a data science resume should include and second on the resume templates that may work well to include the details.
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["AI", "data science", "R", "Go", "Git", "GitHub", "GAN", "programming_languages:R", "programming_languages:Go"]
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.