This rampant growth in the use of data and analytics across most industries and domains has resulted in unprecedented growth in the role of a Data Scientist. As an educator and analytics leader, it’s been exciting to watch the growth in popularity and respect of this discipline. Some worrying trends, however, have emerged.
The surge in popularity of Data Science as awakened or stirred in many an interest in data analysis, modelling and coding, but it’s also attracted self-proclaimed gurus who are desperate to cash-in on those looking for a short cut to the discipline.
There are also many who profess that anyone can become a successful and respected Data Scientist with little or no formal training in mathematics, statistics and computer science and that they can help them become self-educated professionals. Many of these charlatans don’t have sufficient training and experience themselves, so how can they possibly educate others?
From an organisational perspective, technical credibility is vital, of Data Scientists and their manager.
What many people don’t often openly discuss is that their Data Scientist’s sometimes lack sufficient and appropriate training and skills ie they’re simply not up to the task – and the impact this has on the organisation. This can not only reflect poorly on the manager and their team but also greatly inhibits their ability to add value to the organisation, as a result of unrealised potential.
My point is twofold, employing the old Descartes adage:
A question that I’m often asked is, should I do a PhD?
For anyone interested in pursuing a career in research or academia, then post-graduate studies are basically mandatory. Beyond this, there’s also a strong appetite for professionals in industry and government who hold PhD’s, especially in the most popular organisations. Simply put, doctorate studies show that you’ve attained a level of technical competency that’s difficult to match, let alone achieve in the industry, and given the competition for talented candidates, and the nature of certain roles, having one will offer you opportunities that you wouldn’t otherwise have.
From a manager’s perspective, here’s what I usually look for when recruiting for a Data Science team:
Dr Alex Antic is a trusted and experienced Data & Analytics Leader, Consultant, Advisor, and a highly sought Speaker, Trainer & Advisory Board Member.
He has 18+ years post-PhD experience and knowledge in areas that include Advanced Analytics, Machine Learning, Artificial Intelligence, Mathematics, Statistics and Quantitative Analysis, developed across multiple domains: Federal & State Government, Asset Management, Insurance, Academia, Banking (Investment and Retail) & Consulting.
Alex was recognised in 2021 as one of the Top 5 Analytics Leaders in Australia by IAPA (Institute of Analytics Professionals of Australia). He also holds several senior advisory roles across industry, government, start-ups and academia.
His qualifications include a PhD in Applied Mathematics, First Class Honours in Pure Mathematics, and a double degree in Mathematics & Computer Science.