Job Role: Data Scientist
What is Data Scientist?
To help shaping or meeting specific business needs and goals effectively, Data scientists are responsible for discovering insights from massive amounts of structured and unstructured data. As today’s businesses rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies, the data scientist role is becoming increasingly important.
The data scientist role
Very often using software specifically designed for the task, a data scientist’s main objective is to organize and analyze large amounts of data. It needs to be easy enough for all invested stakeholders to understand — especially those working outside of IT.
The final results of a data scientist’s analysis needs to be very easy enough for all investors, shareholders to understand — especially those working outside of IT domain.
His approach to data analysis actually depends on the specific requirements of the organization or department he is working for. Business heads or department managers must describe what they are looking from the data scientist. As such, a data scientist must excel in translating the company or department requirements into data-based output such as pattern detection analysis, prediction engines, optimization algorithms and the like.
Data scientist responsibilities
Data analysis is the prime responsibility of a data scientist. The analysis process primarily starts with raw data collection and ends with dependable business decisions made on the basis of data scientist’s ultimate data analysis output.
The data, drawn from a number of sources — analyzed by the data scientist very often called as big data. Structured data and unstructured data are the two distinct types falling under the umbrella of big data. Structured data is well organized, which is computers can sort, read and in general divided by categories. These are not collected from human input and includes bank accounts or GPS coordinates collected by your smart phone or website traffic data, sales figures etc.
On the other hand, the fastest growing form of big data is the unstructured data. This is more likely to fetch from human input — social media posts, customer reviews, emails, videos, etc. This is less efficient to manage with technology and more difficult to sort through. This may require a big investment to manage since this is not streamlined.
Typically, business houses employ data scientists to manage this sort of unstructured data, whereas other IT personnel will be deployed for managing and maintaining structured data.