According to the US Bureau of Labor Statistics, data science jobs are growing at a 15% rate from 2019 to 2029, which is much faster than any other industry.
It means that there are a lot of opportunities for data scientists. But, the competitions have also doubled.
In this fierce competition, the only way to get shortlisted for a job is by creating a stellar resume that grabs the recruiters’ attention.
This blog will tell you five best practices to write a job-winning data science resume for 2021.
Choose the Correct Resume Format
Recruiters are least concerned about your experience 5-6 years ago. They are more interested in your recent achievements and skills since the data science industry is rapidly changing year by year.
To showcase your latest achievements to the recruiters, you need to write the professional experience section in reverse chronological order.
However, if you have a career gap or are trying to switch your industry, it is not wise to use the reverse chronological format since it will highlight your career gap upfront.
Instead, use a functional resume format. These are skill-oriented resume formats that focus more on your core and transferable skills than your years of experience.
Write an Optimized Data Science Professional Experience Section
The professional experience section showcases all your skills and accomplishments to the recruiters, making it the most crucial section on the data science resume.
You need to make sure that this section is well-crafted and perfectly conveys your skills and expertise to the hiring manager.
Here are a couple of tips to write an excellent professional experience section of a data science resume:
- Always use single-line bullet points to write your functions and expertise in the professional experience section.
- Always write the work profiles in reverse-chronological order
- Always try to back up your statements with numbers and statistics. For example, “Developed data science models to analyze structured data for understanding business requirements; led to a 12% business growth.”
- Club 2-3 bullet points under one subheading. This way, the professional experience section becomes more scannable by the recruiters. For example, for a data science profile, the subheading can be named “Data Mining & Analysis” or “Data Collection & Visualization.”
- Create the bullet points using the cause & effect formula. This way, the recruiters will have a clear picture of your experiences.
Write a Professional Data Science Summary
Recruiters spend on average 7.4 seconds to screen a resume. And in this short time, if you want to grab the recruiters’ attention, you need to create the resume summary section with utmost care. It highlights your skills and accomplishments to the hiring manager; it also helps them understand your years of experience.
Here are some tips for writing a perfect resume summary for a data science resume:
- Place the resume summary at the top of the resume, below the resume title.
- Wrap up the resume within 3-4 lines.
- Start the resume summary with years of experience following the designation.
- Do not use first-person or second-person pronouns in the resume summary.
- Always start the resume summaries with “adept at,” “skilled in,” “Proficient in,” etc.
Here is an example of a resume summary for your reference:
“5+ years experienced Certified Data Scientist possessing skills in solving real-world business challenges using data modeling and analysis. Proficient in deploying complex machine learning and statistical modeling algorithms to identify and mitigate gaps in products or services as part of improving business offerings. “
Create a Separate Key Skills Section
Having years of data science experience is not enough to get noticed by the recruiters. You need to know how to effectively showcase your skills to the hiring managers to make them interested in your profile.
The best way to do this is by creating a separate “Key Skills section in your resume, highlighting all the core and transferable skills you possess.
And in a Technical Skills section, add all the tools and frameworks you have learned in your professional career.
Optimize The Resume Title
It may not look like it, but the resume title also plays an essential role in getting noticed by the hiring managers. Here are some tips to keep in mind when writing a resume title for a data science resume.
- The resume profile title should be placed directly under the resume header.
- Do not write “Resume” or “CV” as the resume title. It does not give the right impression.
- Do not write “Fresher” if you do not have experience, instead write the job title you are applying for.
- Include your designation if you are an experienced professional in the profile title section.
Some ideal examples of data science resume profile titles are:
“Junior Data Scientist
Data Science Intern
Certified Data Science Professional”
Key takeaways
Here are a few key takeaways:
- Only the data science resume summary should be written in paragraph format. Everything else must be written in single-line bullet formats.
- Bold important words and numbers on the professional experience section to highlight them to the recruiters.
- Write the data science resume in reverse chronological resume format unless you have a career gap or switch careers. In that case, go for a functional resume.
- Identify keywords from the job description and include them in the key skills section and professional experience section. It will help you get past the ATS systems.
- Start the resume summary with years of experience and include only relevant skills and accomplishments.