In an era where the world produces such vast amounts of data daily, it is no surprise that the job of a data scientist is in high demand. Big data is a valuable resource of information that can help businesses, organisations, and researchers in their work. The analysis of data allows people to make informed decisions such as strategising, developing new technology, and more. Not just anyone with a basic understanding of math or statistics will be able to handle the large datasets. That is why we need trained specialists in data collection, organisation, and analysis to do the job.
What do data scientists do?
A data scientist is someone who may do one or more of these as the main part of their job: data collection, data analysis, data interpretation, developing data analysis tools and proposing data-driven solutions. Typically trained in statistics, math, computer science, business, or economics, data scientists need to be well-equipped with various skills.
Data scientists can be specialised for different fields and industries. For example, some analyse data for the purposes of assisting marketing strategies in e-commerce businesses. Others analyse data to study human behaviour in relation to internet use.
Who can be a data scientist?
Before you embark on learning the subjects related to data science, you must determine if data science is for you.
- A passion for data
Firstly, you should have a passion for data. This means having a drive that makes you curious about data. An inquisitive mind is necessary for you to gain fulfilment out of the job. With the passion for finding out about the data you have, you will be motivated to find the right methods to analyse and interpret it.
- Organisationskills
Strong organisation ability is also needed to stay on top of your game. Big data is definitely not a small matter. Sometimes, the data points are more than you can count – yet you need to make sure that you use the correct data, and perform the proper steps to analyse them. In this line of work, organising your data is crucial to facilitate efficient and secure work.
- Perseverance
A spirit of perseverance is necessary for being a data scientist. There is no fixed formula for all the kinds of data in the world – sometimes you have to try different methods before you reach a meaningful result. Adding to that, dealing with data can be frustrating due to the coding processes required to manage the data. Perseverance is needed so that you keep going despite making mistakes at first.
How you can become a data scientist
To become a data scientist, most people follow a 3-step path. First, study for a degree in IT, math, computer science, business or a related field. Then, work for a master’s degree in data or a related field. Finally, look for job or internship opportunities to gain experience in data science. In the competitive world of data science, it is almost impossible to launch your career without at least a degree qualification. In fact, the majority of data scientists have a graduate degree, and those that rise to leadership positions typically hold a PhD.
However, if a full-on university education is out of reach for you, the next best thing you can do is to enrol yourself in a dedicated data science course. These intensive courses will equip you with industry-relevant data science skills, increasing your employability in a data science field. A data analytics certification in Singapore will prepare you for jobs that require data analytic skills in various industries.