The Role & Responsibilities of a Data Scientist

The Role & Responsibilities of a Data Scientist

The progress in data science, artificial intelligence, and big data analytics has produced a high number of job opportunities for people who wish to make a successful career in these areas. It is believed that the United Kingdom alone will be responsible for creating 56,000 data science jobs every year from this moment until 2020. Also in a recent research by Hired it was found out that the average salary for data scientists is 56,000 in the UK and $129,000 in the USA. For this reason, a lot many institutes have begun to offer a variety of data scientist certifications and degree programs to aid people to get gain superiority over their competitors. Due to such developments in the field of data science, there has been eagerness among people to know about the roles and responsibilities of a data scientist as well as the qualifications needed to become one.

So, what does a data scientist do?

Data scientists can come from different educational or work experience backgrounds, however for them to be effective in their field it requires them to have proficiency in four primary areas that include business domain, computer science and software programming, statistics and probability, and written and verbal communication.

Apart from the skills in these four fundamental areas, a data scientist also combines analytics skills, machine learning, and data visualization skills to utilize enormous volumes of data available to businesses to make predictions to help them make accurate decisions and leave their competitors behind who could not have the same insights.

One of the key responsibilities of a data scientist is to search for the specific problem and resolve it to deliver impact to the business. To carry out this task, there comes a need for structuring the data in the correct manner, data mining, creating suitable assumption, constructing correlation models and inquiring the data to find anything that can add value to the organization in any possible fashion. The data that is analyzed by data scientist, often called big data, comes from diverse channels.

This data can be structured as well as unstructured. The structured forms of data are easy for computers to read, organize and sort. For instance, sales figures, website traffic data, or GPS coordinates that are collected by smartphones these days are all structured data. Unstructured data, on the other hand, cannot be easily sorted out or effectively managed with the help of technology. All the data that come from human input such as emails, social media posts, videos, customer care reviews etc. are forms of unstructured data.

So, organizations mainly employ data scientists to handle this unstructured data, while the structured data is managed and maintained by IT personnel. There are various ways to become a data scientist and the most common way to go about it is to have a bachelors degree as well as a masters degree. However, this isnt the case with every data scientist as there are other ways as well to attain data science skills such as by pursuing a big data scientist certification. Before deciding anything you should be sure about the industry you would like to join as each industry has its own requirements.


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