The finance industry is banking on AI -- and they're creating new jobs to bridge the gap. Traditional financial institutions and fintech start-ups alike are looking for more candidates who specialize in artificial intelligence, machine learning and data science. According to reporting by Bloomberg reporting and data from LinkedIn, job listings requiring these skills in the financial industry increased nearly 60% in the past year. According to Glassdoor data, "some of the most common job openings in AI and finance are for machine learning engineers and data engineers, among other highly specialized software engineering roles," Glassdoor senior economist Daniel Zhao tells CNBC Make It. "We're also seeing job openings for workers who can help navigate the AI landscape, including consultants and researchers. As companies establish the foundations for their AI functions, we're seeing employers hire more senior candidates to lead these new teams."
"AI and machine learning will undoubtedly alter both the headcount and the nature of skills required in the industry. A significant minority of survey respondents fear the effects on the workforce will be negative within the next few years. But wholesale displacement of humans is for the longer term – nearly seven in ten believe AI will bring complete or substantial change to their own jobs over the next 15 years…" A while ago, I wrote that AI and machine learning was more and more used in our daily lives – but that finance had so far failed to embrace these techniques. Euromoney Thought Leadership just published a very interesting report, where they surveyed 400 senior managers in finance and analysed their views about AI. I was actually slightly suprised by the results: the majority of participants thought that the main impact would be on 1) trading strategies, 2) credit scoring and 3) compliance.
Quandl's a great portal for finding economic and financial data, which is useful for building models to predict economic indicators or stock prices. To download data, you'll need to register on the site. Exporting data in Python also requires you to download the Quandl Python Package. It's also worth noting that you'll need to filter to'free' to list the free financial datasets, otherwise you'll need to purchase a licence (costing $1200) to access premium datasets.
Finance teams are integral and essential to the smooth running of any business. The role of the finance team is beginning to increase in scope, and this means that finance professionals are beginning to be concerned about what they can't see or control. Finance teams of the past have left the company's decisions around implementing new technology to others, seeing it as beyond their remit. If the IT was not broken, then the finance team was certainly not looking for a way to fix it. Now, however, the situation has changed.
The following is a follow-up guest post by Jeremy Epstein, CEO of Never Stop Marketing, to his previous articles on blockchain marketing and blockchain brand promises. Jeremy currently works with several of the leading companies in the blockchain and decentralization space including OpenBazaar. Previously, he was VP of marketing at Sprinklr.