Editorial

7 Pro-Tips to Incorporate While Creating a Professional Machine Learning Resume

Simply possessing the skills of an efficient machine learning professional is not enough to get you hired by the company you’ve been dreaming about. 

In today’s AI driven world, you need to be able to showcase those skills in your machine learning engineer resume in a way that is appealing to the recruiters and the ATS (Application Tracking Software) system that they use to select the best resumes. 

A job winning resume calls for a detail oriented approach. It has to meet the current industry standards and an outdated resume just won’t cut it. 

Follow the Reverse Chronological Format 

When drafting your machine learning resume, ensure that you are following a reverse chronological format which presents your most recent work experience at the beginning, followed by your former roles. 

Reason being, this is the universally accepted format preferred by both recruiters and the ATS system (more on that later).

It also makes your resume more relevant and up to date. 

Use ATS Friendly Keywords

ATS stands for Application Tracking Software. Believe it or not at least 99% of Fortune 500 companies use this software to scan and filter out the best suited resumes. 

Therefore, using keywords that will allow your machine learning resume to rank high in the ATS system is extremely crucial if you want to get hired. 

You must read and pick out the keywords from the job listing and include it in the skills section of your resume.

Segregate Your Key Skills and Technical Skills 

Your key skills as a machine learning professional should ideally be backed up by the professional experiences you possess. 

Some of the common key skills for a machine learning professional includes:

  • Data Analytics 
  • Web Scraping 
  • Data Mining 
  • Training and Mentoring and so on

Meanwhile, your technical skills must include all the software and program languages that you are efficient in. 

Here are some examples: 

  • Tools: Python, PostgreSQL, AWS, Hive
  • Packages: NumPy, SciPy, BeautifulSoup

Use Power Verbs

Using power verbs to begin each line in your professional experience section amplifies the impact of the information you are presenting. 

In other words, it is more impressive to the recruiters. 

Start your sentences with words like designed, developed, managed, created and so on.

Frame effective one-liners

As it is, the recruiters don’t spend more than 6 seconds on a single resume. And if your resume has nothing but bulky paragraphs, there is no way that recruiters would want to sit and read it all. 

Hence, your machine learning resume should consist of one-liners and bullet points that effectively convey the information you are trying to present. 

Quantify Your Achievements 

If you want your achievements to stand out in your machine learning resume, you must give a number or percentage to your achievements. 

An exact number or percentage solidifies your success and gives the recruiters a clear picture. 

For instance, writing “Increased the accuracy of a machine learning model” seems quite flat and doesn’t really create much of an impression. 

However, presenting the same information with a percentage figure immediately draws a much clearer picture for the recruiters. 

“Increased the accuracy of a machine learning model by 100%”

Keeping Your Resume Crisp

The universally accepted length of an ideal resume is only a page long. That’s why it is important to make the best use of that single page and make your machine learning resume crisp. 

The information you present must be to the point and it’s vital that you don’t present irrelevant information on your resume and lengthen it unnecessarily.

The only exception here is if you are a candidate with 10+ years of experience.

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