Are you looking for a Data Science Job but not getting any interviews? Then you need to make a strong data science resume. Don’t worry I will tell you how to make a strong Data Science Resume. Give your few minutes to this blog and understand how you can make a powerful resume that will help you to get hired.
Hello, & Welcome!
In this blog, I am gonna tell you-
So, Let’s get started-
How to Make a Data Science Resume?
Step by Step Process to Create a Resume
I am assuming that you have enough knowledge in the Data Science field. So the very first step in resume making is- Template Selection.
Before writing a resume, you need to find out a template for a resume. For a data science or machine learning resume, choose a very clean and simple template.
Things you need to remember while choosing a template-
- The template should be classic.
- Avoid templates with so many graphics. It gives a bad impression to the recruiter.
- Don’t hesitate about white spaces. That means don’t try to fill the full page with text. Leave some white space that looks clean.
- Text size is also very important. It shouldn’t be very large not too small.
- Choose the Font which is simple and classic like Times New Roman.
- Don’t write a long text like a story. It should be precise and simple.
- Try to end up on one page because recruiters give only 30 seconds to your resume. You need to impress him/her in a 20-30 second span of time.
- If you are an experienced guy having experience in different companies and found it tough to put all details on one page. Then don’t need to write all the experience details which are not relevant to the machine learning field. Only list relevant experience in the resume.
NOTE- Most of the companies are using ATS( Applicant Tracking System). This is an AI-based system which screens lots of resume in less time. So for ATS, a single-column resume is the best bet because it is easy to understand.
Therefore, after choosing a perfect template for your resume, the next step is what information you need to put on your resume.
So, now I am gonna tell you what information you need to write in your resume-
- Career Objective.
- Projects or Publications.
- Skills and Certificates.
In the Header Section of your resume, you need to write your name and contact information. This should be at the top of the page. While writing a header part of a resume, you need to take the following things in your mind-
- Remove the title “Resume” from your resume template.
- Write your name in place of the “Resume” title.
- After writing your name, just describe yourself who you are? in a few words. For example, if you are a software engineer and applying for a data science job, then don’t write a “Software Engineer”, write “Data Science Aspirant” or any other role in which you are applying.
- Don’t write full physical address, just write City and State.
- Always make sure, what phone number you are writing is on working conditions. So that recruiters can easily contact you.
- Don’t write a personal email id. Personal email id means that looks something like that [email protected]…LOL… 😀. A Formal email id means [email protected].
- Give your Linkedin profile link and Github link. So that recruiter can have a look at your projects whatever you have done. And make sure these links are clickable so a recruiter doesn’t face any issues while opening your link.
2. Career Objective.
A career objective defines your motivation. It should be simple and cut to cut. If you are fresher, then you should definitely add a career objective in order to show your passion for the field.
While writing a career objective you need to take care of following things-
- Your career objective should be an attention seeker.
- In your career objective, you should give brief information on your skills.
- Don’t write a very long Career Objective, which bore the recruiter.
3. Projects or Publications.
In this section, you need to write what you have done previously in Data Science Field. Whatever projects you have done like data analysis projects or machine learning projects, you need to write these projects in this section. You can also mention your published papers in the data science field.
Some do’s and don’t for writing projects in Data Science Resume-
- While writing about the project, mention tools used, the technology used, algorithms used. Write all the details regarding your project.
- Not only explain about the project, but you also need to show the impact.
- Don’t add very simple projects. Only add those projects which will give a good impact on the recruiter.
If you are an experienced guy, then you need to write the experience details in that section. You should write the most recent experience first. If you have more than a five-year experience, then no need to list all the details. Just write the relevant experience which suits the job profile.
Suppose you worked for one year in your father’s supermarket as a manager. Then don’t need to write this experience in the resume. But if you have worked as a Data Analyst in your father’s supermarket, then you can mention it on a resume.
One more important thing, if you have more than a six-month gap in your career, then you need to mention the reason.
If you are fresher, then you might be thinking what should I write in this section? well… no worries. You can also write the following things in the Experience Section.
- You can mention any internships, which you have done in Data Science. No matter, you have done from any reputed company or from a small place. You can mention along with the internship period plus what you have done.
- You can also mention your college projects that include data science work. When you were learning data science you have done some practical exercises, you can also mention them.
- Mention your volunteer work related to data science.
The next section is education. You can showcase this section first, but if you have done various projects and you have experience in data science then put them first. But if you are fresher, then you can put the education section first then projects.
Following dos and don’ts regarding education section-
- Only mention a college-level degree.
- Don’t add schooling details.
- Don’t list micro-degree like online training.
- Include your GPA and the final marks.
- Mention the key courses which suit the job profile.
- Don’t afraid to write a long education section, because it gives a good impact.
- Mention your graduation or post-graduation year with your degree.
6. Skills and Certificates.
In this section, you need to mention the suitable data science skills you have. The skill section is mandatory for technical jobs. So you can’t avoid this section.
Dos and don’ts for writing Skill section-
- For Data Science Job, you need to write only those skills which are required in data science like Python and Machine Learning.
- Don’t write skills like leadership quality and something like that.
- Don’t give a rating or numbering on skills.
- Write your strongest skills first, so that recruiter will focus on that part.
- Write only those skills which you have. I have seen many people writing skills which they don’t have. Just for showcasing. But this will harm you in the interview process. This will make a bad impression when the interviewer asks you some questions on the listed skills but you can’t answer. So make sure, write only those skills, which you know very well. This is very important.
- Mention skills like- Python, Numpy, Pandas, Data Cleaning, Data Visualization, Probability Statistics, and etc.
- Read the job profile and what skills they require, then see how many skills you have. Suppose in the job description they mentioned Good Knowledge of Python, and you have good knowledge in Python, then definitely write “Good Python Knowledge” as the first skill. You can repeat the same for other skills too, just compare your skills and the skills written in the Job Description.
- If you have done any certification courses on Data Science Or Machine Learning then also mention them in your resume.
After finalizing your resume, you need to check for grammar and spelling mistakes. You can give your resume to your trusted friend. They can check for grammar mistakes. But if you don’t wanna give it to your friends then you can check it on Grammarly. Because of any grammar or spelling mistakes, your full work will be wasted. So thoroughly check for grammar and spelling before sending it to the company.
One more thing I would like to tell you that most of the companies are now using ATS (Applicant Tracking System), which is an AI-based system that parses your resume and then sends it to the recruiter. So getting selected in parsing is very important if a company is using ATS. So for that keep your resume in .doc format, not in .pdf format. Because the .doc format is easy to parse.
I hope now you have a clear idea about Data Science Resume. Now no one can beat you to come in Data Science Field. Make Your Resume Today.
All the Best!
You May Also Interested In
15 Best Online Courses for Data Science for Everyone
Data Analyst Online Certification to Become a Successful Data Analyst
8 Best Data Engineering Courses Online- Complete List of Resources
Best Course on Statistics for Data Science to Master in Statistics
8 Best Tableau Courses Online- Find the Best One For You!
8 Best Online Courses on Big Data Analytics You Need to Know
Best SQL Online Course Certificate Programs for Data Science
7 Best SAS Certification Online Courses You Need to Know
Data Analyst Online Certification to Become a Successful Data Analyst
15 Best Books on Data Science Everyone Should Read
Though of the Day…
‘ It’s what you learn after you know it all that counts.’– John Wooden