Employability and data science
There is general agreement that employment is changing. There is, however, much less agreement about precisely how it will change, although plenty of crystal-ball gazing has gone on. A study published by the World Economic Forum in 2016 suggests a rather nuanced situation with employment fluctuations likely to vary considerably by sector, type of job and geography.
The job market to 2020
Overall, various factors are expected to have very different effects on the employment market up to 2020. For example, young demographics in emerging markets could boost employment by around 5% globally. At the other end of the spectrum, geopolitical instability is predicted to decrease employment by 2.7% . Artificial intelligence, much hyped for its likely effect on jobs, stands to have a rather smaller effect: around a 1.5% reduction.
However, these overall figures mask considerable differences by sector and job type. In computing and mathematical jobs, for example, employment is estimated to increase by 3.2%. Most big factors affecting that sector are technological, although geopolitical instability also features, and all these changes are expected to have a positive effect on employment levels. This suggests that even instability is likely to result in more demand for modelling, programming and general computer power.
Coupled with these changes is an expectation that recruitment will get harder. Across every sector and every job family, without exception, the perception is that recruitment will be more challenging in future.Across every sector and every job family the perception is that recruitment will be more challenging in future #ai #sasacademic Click To Tweet
The graduate recruitment market
How do these varying trends across sectors affect the graduate recruitment market and what other elements should be factored in? Besides trends that affect the overall job market, an important factor is the number of people applying to university, because this affects overall student numbers and graduate numbers. For example, in the UK university applications have fallen this year, a development seen by some experts to be a result of Brexit.
According to studies, the gig economy is also likely to affect graduate recruitment. Overall, graduates see the gig economy as positive, but the lack of benefits such as annual leave is a deterrent. However, technology graduates see the gig economy might offer a way, at least in the short term, to earn more money because of the skills shortages in certain areas. With student debt an ever-increasing problem for many, regardless of nationality and geography, this could be a serious incentive.
Graduate jobs are also changing. For example, AI could result in growing numbers of entry-level jobs being automated, which will probably mean fewer jobs. Many employers are also converting graduate-level jobs into apprenticeships, especially in the UK where this attracts a government levy. This trend also illustrates the ‘training’ nature of many graduate jobs, with employers saying that graduates’ soft skills in particular require development to match the required hard skills.
Employment is not the end
Undergraduate and postgraduate students may see getting a job as the end of their education, but employers will see the situation very differently. For them, employment is just the start of the process of ongoing training to ensure that their workforce has the required skills. This is particularly true in shortage areas like data science, where graduates may be in short supply. Here, encouraging your existing workforce to improve their skills is a very good way to acquire the required know-how.
Postgraduate study is now an established route into a career as a data scientist. It is however certainly not the only option. There are a number of training options for data scientists and since the field is rapidly evolving, continuing professional development is essential to remain up-to-date with new tools and techniques.
Online study options are often popular, because they allow learners to do courses in their own time and at their own pace. Learning can also be applied to the job straight away so benefits are immediate, and it is then easier to persuade employers to fund more training. Online learning may also be more up-to-date. Platforms like DataCamp are popular because many of their courses and tutorials in data science tools in particular, are led or provided by the creators of those tools.
Rapid development requires rapid reaction
It is certainly true that change is all around in the employment market. The speed of change in a discipline like data science means those in the field must remain aware of changes. Perhaps the most desirable quality in a new data science hire is their dedication to continually learn more.The most desirable quality in a new #DataScience hire is their dedication to continually learn more. #sasacademic #ai Click To Tweet