The demand for machine learning talent has exploded in recent years. And there’s a growing need for companies to hire the best candidates for the job.
Your machine learning skills section is a great way to stand out and get hired.
Here are the machine learning skills every recruiter will look for in your resume:
See how to use Machine Learning skills on your resume:
Types of machine learning skills to add in your resume:
- Data modeling and evaluation
- System design
- Programming languages: C, C++, Java, Python
- Software engineering
- Data analysis and interpretation
- ML libraries & algorithms
- Signal processing techniques
PRO TIPStill struggling to determine your most marketable machine learning skills? Write down as many skills as you can think of. Then, cut all the basic, repetitive ones. And only keep high-demand, industry-specific abilities that will get you hired.
How to demonstrate Machine Learning skills on your resume
- Selected machine learning libraries for different tasks
- Designed new models and algorithms for machine learning projects
- Implemented machine learning experiments that lead to the development of new algorithms
What jobs require Machine Learning skills:
- Data Scientist
- Software Engineer
- Data Analyst
- Software Developer
- Data Science Intern
- Research Assistant
- Web Developer
- Machine Learning Intern
Read our article on how to add language skills on resume for additional tips and tricks.
Machine Learning skills courses and certificates:
Here are the top related skills to Machine Learning:
Machine Learning popularity over time:
Courtesy of Google Trends
For a deeper look into what’s the best resume format for you based on experience, check out our guides:
About this report:
Data reflects analysis made on over 1M resume profiles and examples over the last 2 years from Enhancv.com.
While those skills are most commonly met on resumes, you should only use them as inspiration and customize your resume for the given job.