Thomson Reuters (NYSE/TSX: TRI), a global content and technology company, released its Future of Professionals Report. The survey of more than 1,200 individuals working internationally shares the predicted impact that generative AI will have on the future of professional work.
Thomson Reuters Future of Professionals Report Predicts AI will Have a Transformational Impact on Professional Work by 2028
How AI Can Prevent Rising Candidate Fraud
Candidates are lying and cheating to get hired more than ever. INSIDER recently cited a study, “The Future of Candidate Evaluation,” by our friends over at Glider AI that found candidate fraud has nearly doubled since before the pandemic. As INSIDER reported, more companies believe AI is the solution.
New O’Reilly Report Reveals Nearly Two-Thirds of Data & AI Professionals Prioritize Job Training in Hopes of Salary Increase
Reilly, a premier source for insight-driven learning on technology and business, announced the results of its 2021 Data/AI Salary Survey, which revealed that 64% of respondents took part in training or obtained new certifications in the past year to build upon their professional skills.
Competitive Tech Companies Lead with Culture to Land Top Talent
In this contributed article, Danielle Jones, Director of Service Operations with Insperity, discusses how competing for high-caliber talent is one of the biggest challenges faced by tech companies of all sizes. With a strategy to prioritize company culture and cultivate a meaningful and positive employee experience, small and midsized data companies can get a head start when it comes to competing with their Big Tech counterparts.
Mistakes to Avoid When Starting a Career in Data Science
In this contributed article, IT and digital marketing specialist Natasha Lane, highlights how the shortage of data science talent is dramatic, but there are still a few mistakes you can make getting your foot in the door. These are the types of mistakes that can slow down your initial career progress, so the article covers them to help you make sure you’ll avoid the pitfalls.
Panel Discussion: Needed Data Skills for 2021
In this panel discussion article, Grant Shirk, Head of Marketing at Sisu, to help both hiring managers and job seekers looking to fill these key roles, sat down with a number of senior analytics leaders to get their perspectives on hiring, recruiting, and critical skills. You’ll find their conversation below, full of insights and actionable recommendations.
Chatbots for Recruiting
Talent departments are spending $250 billion on recruitment, interviewing and candidate assessment solutions. But as employers invest in these disparate technologies, they sacrifice efficiency and deliver a disconnected experience throughout the talent lifecycle. Enter the AI chatbot. Phenom, a leader in Talent Experience Management (TXM), is a single platform that individualizes the end-to-end talent journey for candidates, recruiters, employees and management.
Infographic: How to Become a Data Scientist in 2020?
Data Scientist continues its reign as one of the most coveted jobs in 2020. In fact, as the business world becomes increasingly data-driven, there is a serious concern that the data science skill gap will continue widening and the supply of data scientist career talent won’t be able to catch up to the industries’ demand. For the 3rd consecutive year, our friends at 365 Data Science asked the data and collected their findings in a detailed annual report summarized in the included infographic.
Interview: Mike Hudy, Ph.D., Chief Science Officer at Modern Hire
I recently caught up with Mike Hudy, Ph.D., Chief Science Officer at Modern Hire, to discuss the use of AI in the hiring process. Hint: it includes a robust and specific code of ethics, implementation with a specific problem in mind, and lots of transparency.
What Employers Should Consider in Big Data Hiring
In this contributed article, freelance human Avery Phillips discusses the many things you need to consider when hiring for big data. Thinking about the nature of your organization, the potential roles, and responsibilities of your data employees, what you aim to achieve through the use of big data, and finally, considering budget; is a good place to start when it comes to big data hiring.