5 Creative Strategies to Recruit Machine Learning Talent
By Kelly Barcelos
January 18 2021 - Machine learning (ML) is one of the many subsets of artificial intelligence. It is also on the path to becoming one of the most in-demand skills. This has led to fierce competition amongst hiring managers to find the right talent before someone else does. You need to get creative with your recruiting strategies to find the best possible talent.
1. Know What to Look For
It is common to look for the right experience when you hire someone. However, you must go beyond that metric and look for important skills while hiring employees for a machine learning role.
Look for someone who has a background in statistics and mathematics. This educational background will enable ML talent to understand and identify the right algorithms to address business issues.
Apart from education, you want someone who has a great ability to understand data and derive meaning from it. An innate sense of creativity and curiosity would be a bonus. Lastly, the candidates must be able to grasp new concepts easily so that they evolve in their role.
2. Teach Old Candidates New Tricks
If you cannot hire the talent with the exact skills, look for candidates who possess related skills. You can then teach them the necessary ML skills. Identify those who are well-equipped to learn and develop machine learning skills.
For instance, look for candidates who have great data-mining abilities or proficiency in programming languages such as Java, Python, R or C++. They are not prerequisites to work in ML field but such candidates will surely have the chops to learn ML skills. Spot professionals with engineering, computer science, and IT backgrounds.
With the right training, those people can be a valuable addition to your machine learning team.
3. Tap Into Different Industries
Apart from the core machine learning field, you can find machine learning talent in other industries. For example, 33% of those in the field of higher education and research possess ML skills. Almost 26% of software and internet industries have machine learning talent. The finance and banking, and management consulting industries claim around 7% of machine learning talent.
Professionals with ML skills may consider switching industries to put their knowledge and skills to use. You can expand your talent pool by looking beyond your industry.
4. Provide Talent with Opportunities to Switch Jobs
It can be challenging to find and attract the right ML talent. This is why you need to provide opportunities that can motivate in-demand talent to switch to ML jobs. You can attract such candidates by offering them competitive compensation, challenging opportunities, resources, and brand recognition.
You don’t have to be a huge company to offer talent competitive compensation. If you feel you cannot do that, try offering long-term benefits and perks. Consider giving the option of working remotely if you are located in an area where attracting candidates is difficult.
Assess all the opportunities that can motivate ML talent to switch jobs. Offer the right incentives to recruit the talent that would otherwise be out of reach.
5. Team Up with Educational Institutes
You can tie up with educational institutions or support a school project so that it opens a pipeline of ML talent. You can bring in the talent as paid interns or offer them a full-time employment role.
Before you approach any university, plan the project properly so that you can successfully pitch it. You will have to develop an exciting project so that you can attract interested students.
A final word: By following these strategies, you can increase the odds of finding the right candidate. You will have a bigger talent pool to choose from and find the right hire for your needs.
About the Author
Kelly Barcelos is a progressive digital marketing manager for Jobsoid - Applicant Tracking System. She is responsible for leading the content and social media teams at work. Her expertise and experience in the field of HR enables her to create value-driven content for her readers - both on Jobsoid’s blog and other guest blogs where she publishes content regularly.
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