The need for data scientists is on the rise, but what can you do with a career in the industry? What would your typical day involve?
Data science is still one of the most popular job sectors at the moment and it is replete with opportunity.
Last month, a report showed a 57pc increase in data science roles across the globe in just one year.
While the data science sphere is growing at an exponential rate, many people are still left scratching their heads wondering what exactly a data scientist does or how they can become one.
For a start, the vast majority of data scientists hold a master’s degree, with many also having a PhD.
Data science is a multidisciplinary field that revolves around reading and processing data, pulling knowledge from that data, and being able analyse and explain the information in a comprehensive way.
Data scientists need analytical and mathematical brains to analyse data. They also need technical skills in computer science, end-to-end development and coding. A data scientist should also be comfortable with databases such as MySQL and Oracle.
According to Glassdoor, the average salary for a data scientist with fewer than five years’ experience in 2016 was $92,000.
More than half of data scientists work as researchers, but there are other roles available as developers or in business management.
Once you have the skills required, it’s easy to think that data scientists simply analyse data, but what exactly does that mean? What would your day-to-day job look like?
Some of your responsibilities may include conducting research, extracting huge volumes of data and cleaning that data to exclude irrelevant or unusable information.
Computer programming skills come into play when you are building new systems and algorithms to solve data problems.
One of the softer skills you will need – one that is often forgotten about – is communication skills. Part of your day-to-day job will be to present and effectively communicate the data you have analysed.
With most data scientists working in the technology sector, it can be easy for potential candidates to neglect these soft skills but they are essential for data science. The data you analyse is only as good as how well it’s presented and communicated. Without the necessary skills, you will find it difficult to progress in this field.
For more information on a data science career, check out the infographic below from Rutgers Online.