“It’s a pivotal moment in the IT space," says Jennifer Kling, Director of ERP, CRM and BI Support Services
at TEKsystems. "The demand for talent is 100 percent there. If a company isn’t starting to hire AI, machine learning and data science roles, that company won’t be here in five years.”
If you're an IT pro, we know we're preaching to the choir when we tell you to stay on top of IT trends. But it still makes sense to ask yourself, "What initiatives are IT leaders investing in? What skills will be in demand in the next few years?"
The technological world around us is learning, automating and becoming more efficient. And it's happening fast. IT leaders are expecting to take action and implement artificial intelligence, automation, machine learning and big data initiatives in the next 12–24 months, according to our IT Forecast
Take a peak at what these large companies are looking for and learn how you can capitalize on it.
Industries that are dipping their feet in the AI and big data waters
“Every company has data,” says Amanda Cora, a big data Recruiter for TEKsystems. “But whether there are job openings depends on whether these companies are looking into their data to extract value, for example, to improve business processes.”
Although every company does have data, TEKsystems recruiters and account managers see a pattern in which industries are using the data to develop new strategies. “The industries that are hiring candidates to analyze their data and providing opportunities are mostly retail, healthcare, manufacturing, financial services and transportation,” says Kling. “Companies in these industries are using their data to see how they can automate processes that are prone to error and could cause a massive shutdown.”
Retail companies, for example, are using data scientists to help save money, target appropriate customers, read online traffic or use predictive analytics to make personalized suggestions to customers based on purchasing data.
Companies look for the ideal candidate to push projects forward
Non-traditional backgrounds are celebrated in this space. “Our clients look at candidates with degrees in computer science, data science, engineering, statistics and mathematics. Successful candidates are great at problem-solving,” says Rogers Mason, an AI, machine learning and data science recruiter at TEKsystems.
“We also like candidates with an engineering mindset,” says Cora. “This means that you look at the bigger picture by deciphering data and using predictive analytics to provide solutions and help develop a strategy.”
Another important trait? Business knowledge. "A perfect candidate is a business/analytical hybrid; someone who has an understanding behind the business decisions and also has the analytical skills to slice and dice the information they are finding," says Kling. If you're looking to break into AI and data science roles, don't discount the value of your industry expertise. It may make sense to focus your job search in the industry in which you have the most experience, and make sure to highlight that domain expertise in your resume and LinkedIn profile.
Preparing for AI and big data interviews
To ace an interview for projects in AI and big data, don't discount the importance of seemingly simple questions.
"Explain your last role" is a common request from hiring managers seeking to understand candidates' expertise. "A lot of candidates can't explain the bullets they listed on their resume. Usually their team worked on the project—not them specifically—so employers want to understand the role the candidate played," says Cora. "Go into detail about the role. Where, why and how did you use a specific technology in your last role? Why did you use it over other technologies? Would you have done it another way?"
Another seemingly simple question that reveals a lot about a candidate is, "Tell me about your background in less than three minutes." Being able to succinctly describe your background in three minutes or less shows your ability to provide important information in a cohesive manner. A lot of AI pros and data analysts will need to describe complicated or in-depth information off the cuff. Proving this ability in your interview will give you a leg up on the competition.
The future bright ... if a big vague. "Our clients are laying a foundation for their future," says Kling. "They will always be in the market for candidates who can help the company make adjustments based off data to increase enterprise growth, improve efficiency, improve profitability and decrease supply chain costs."
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