Data science has become one of the most popular and in-demand career paths in the last few years and many companies are looking to hire professionals within the field. This is due to the growing need to harness the incredible value within previously untapped data for business insights. With over 2.5 quintillion bytes of data generated on a daily basis, that’s quite a bit of data to manage and understand to say the very least - and is driving the need for nearly 11.5 million new data job openings by 2026.
A career in data science sounds interesting and promising to many people, but what does a data scientist actually do on a daily basis?
There is no real “typical” day in the life of a data scientist. The very basis of their job means that they must be flexible and adaptable throughout the work day. While working with data, working with people, and keeping up their skills within the field are always required, every data scientist’s role will be different depending upon factors such as business sector and field.
However, every data scientist’s day obviously revolves around the data itself. They spend a large part of their time gathering and shaping data in a variety of different ways for many reasons. These tasks may include looking for patterns and trends, building data visualizations, testing new algorithms, and sharing their results with other team members.
Their real goal, however, is to act as a problem solver for an organization. They work with these large amounts of data to seek to not only determine the questions that require answering, but also to present different ways to solve the issues or questions at hand.
The role of a data scientist does not only require working with data nor is it limited to coding, statistics, and math. As their roles are driven by the need to creating understanding and help with decision-making, data scientists spend quite a bit of time presenting their findings to others in digestible, helpful formats to help businesses and their customers. They typically work across teams and departments to simplify issues for people who are not experts in data, so communication skills are a definitely required.
Learning is also a huge part of the role of a data scientist. Some of their day is typically spent on research and development to help find and test things like new algorithms, build new data models, and develop new predictive tools. To accept a role such as this requires a passion for constant learning and skills updating.
How can someone get started within the field of data science? The answer starts with training.
At Logical Operations, our Data Science Certification Path prepares and gives participants the skills required for a job within the field of data science. Each of our courses builds upon the previous one to help students jumpstart their training and move beyond a role as a data analyst and into a data scientist. To learn more about our certification path, click here or contact us today.