The 4 Most Important Traits to Look for When Hiring an AI Expert

Although AI gets a lot of heat for putting millions of people out of jobs – thanks to its automation properties – it is also creating opportunities for many to start promising careers in data science. Regardless, there can be a lot of roadblocks when hiring an ai expert.  According to a report from the World Economic Forum, demand for AI-related jobs has been on a consistent upward trajectory. This report also predicts that within just six years, 71% of typical work-related tasks will be performed by AI technology – which is why over half of all organizations plan to hire more people with AI-related skills within the next few years. There is little doubt that your organization will be looking to add data scientists and AI experts in the near future – if you haven’t already begun the search. But since this is such a new field, it is often difficult to find a great candidate that you feel confident enough to hire. Furthermore, since AI technology is so complex and developing at a rapid rate, there are many nuances to the position. These can be difficult to assess during the interviewing process. Making such a major hiring decision can have massive repercussions on your business. A bad hiring mistake can cost your company thousands of dollars, whereas a smart one can catapult it to success. So, before you start the recruiting process, make sure that you understand these four basic principles to look for when hiring an AI expert to join your team. [Related Article to Hiring an AI Expert: What are Some of the Best Practices for Hiring Data Scientists?]  

Knowledge in the Top Programming Languages

Depending on the nature of your AI projects, different programming languages will need to be used. Unless you are entirely set on a single programming language and are positive that you will not be using any others, it is best to look for an AI expert that is proficient in multiple coding languages. There is no set checklist that every recruiter should look for to qualify a candidate based on their knowledge. Again, the programming language (or languages) that will be most important are dependent on the types of projects your AI team will be working on. However, these are the most common programming languages that any true AI expert should be familiar with.

• Python: This is the unofficial foundation for programming languages, and just about any data scientist or AI programmer will know how to use Python. It is the most commonly used due to its simplicity and quick development, making it the ideal language choice for projects that are functional as well as procedural – such as machine learning focused systems. It is often used by companies related to IT, engineering, and professional services, and is commonly utilized by Google, Instagram, and YouTube.
• Java: Next to Python, Java is arguably the second most common programming language. It requires high-level training and experience to truly master. It is ideal for web-based development projects and is often used for communication programs, IoT, and cloud computing, as well as video games and apps.
• JavaScript: JavaScript is another popular programming language, as 65% of AI developers report using it on a regular basis for their projects. It often plays a key role in front-end and gaming development. Additionally, it is used by many social media platforms to create interactive pages.
• C/CPP: C dates back all the way to the 1970s and has paved the way for other language derivatives, including Java, Objective-C, C+ and C++. Each variation offers a slightly different focus, but overall, C is often used for higher-level applications – including virtual reality and computer graphics. C is commonly used by Microsoft, Apple, and Oracle for IT and engineering services.

Applied Math Sciences 

Obviously, AI is founded in statistics and algorithms, so be on the lookout for ways that a candidate has experience in applied math, probability, and statistics. There are numerous academic paths that an AI expert may take that will provide them with the mathematical skills needed for a successful career. Of course, a degree in mathematics, computer science, and/or statistics is a great indication of necessary experience in this matter. But, there are other majors and career backgrounds that will have relevant overlaps. Candidates with degrees in engineering or physics will have a strong mathematical background, with the added benefit of focusing on the purpose of statistics and data – which is to explain and predict. It is also necessary for a true AI expert to have both learned skills and experience in algorithms and applied mathematics. This is primarily for accurate data science prediction. Since AI is widely used for predictive tasks, such as data analysis and projection or personalized experiences, it is necessary for the person that you hire to have a deep knowledge of algorithm theory, with a focus on subjects like:

• • Gradient Decent: Iterative optimization used by algorithms to find the minimum of a function by pinpointing the steepest descent of the gradient.
  • Convex Optimization: A mathematical approach for minimizing a convex function over a convex set.
  • Lagrange Interpolation: A formula to find new data points with a known set, used to estimate the value of a function.

• Quadratic Programming: A mathematical optimization problem used to minimize or maximize a quadratic function that contains several variables.

Proficiency with Hadoop

Hadoop takes a starring role in big data storage and data processing, which is why it goes hand-in-hand with AI. It is a common open-source storage and processing framework used by many businesses through the public cloud. Hadoop is especially important for organizations that deal with massive sums of data, such as financial corporations or software companies. Of course, this is not the only storage and processing framework. Spark and Kafka are two other systems that were created after Hadoop, of which offer similar and additional features. During the hiring process, you will most likely want to look for experience and familiarity with Hadoop as a necessary qualification. This framework is very foundational – even if your business utilized other systems. There are several key benefits to Hadoop, particularly in relation to logistic regression performance, making it a smart, solid foundation for any AI expert to have.

https://www.edureka.co/blog/apache-spark-vs-hadoop-mapreduce

Furthermore, Hadoop is written in Java; any expertise in this area will also speak to the Java language capabilities.  

Keep an Eye Out for Soft Skills, Too

There is an exhaustive list of hard skills and educational requirements for positions in AI. But remember, this person will be a part of your team and influence your company’s culture. Great analysts need soft skills, too, especially if they are working face-to-face with clients or in a collaborative office. First of all, communication skills are going to be extremely important for any AI expert to possess. This is for explaining results and turning your company’s vision into a reality. Since not everyone within your company is going to be entirely knowledgeable about things related to AI, Big Data, and IoT (particularly when it involves complex math and formulas), your new data scientist must be able to relay the insights with understandable results. If your projects are centered around collaboration and teamwork, leadership and cooperative skills are also going to be essential. Since this person will likely be heading up any AI-related tasks and projects, they should have some experience and proficiency with leadership and management. Good people skills are also necessary – even though much of their time will likely be spend behind a computer screen. Of course, identifying these soft skills can be tricky during a traditional interview.

[Related Article to Hiring an AI Expert: Here’s Why You Can’t Hire a Data Scientist]

It is quite easy for candidates to lie on their resume or fake a friendlier, outgoing personality – as they are trying to impress the hiring manager. Technology can actually be a great resource to use in this case. There are many AI-powered recruitment programs that use machine learning and predictive technology to create soft skill assessments. These are designed to measure a person’s communication skills, situational judgment, a team mindset, and so on.  

https://www.plum.io/how-it-works

Conclusion

Hiring an AI expert, and making sure you’ve found the right one, will always be a major decision that companies cannot take lightly. This is particularly true when it comes to hiring someone to help your business stay progressive with ever-developing technology like AI. You want to hire the person that will have the most positive impact on your business and help you take things to the next level. Start by looking for necessary skills, educational backgrounds, and experience that all point to the necessary knowledge and proficiencies in this area. But don’t forget to consider the soft skills, too. After all, this person will be playing an important role as a team player – both now and in the future.