Top 5 Data Scientist Skills You Should Have in 2022

Who are data scientists? What do they do? years ago, data scientists did not exist. People within the organization perform data mining, data cleaning, and analyse data as per business needs. But today’s digital world has taken a 360-degree turn and data/information has become a vital asset for organizations.

One of the most in-demand fields in 2022 is Data scientist. Now the data scientist profession that we admire today is standing at the head of the new career path. Modern data scientists have combinational skills including technical know-how with expertise in analytics along with curiosity and problem-solving skills.

Since it is one of the desired fields in recent times, the competition rate is a little higher than other fields. People face tough times to get hired as data scientists.

So what you can do to improve your chances to get hired, here are the top 5 skills to get hired as a data scientist:

1- Critical thinking and problem solving:-Critical thinking is not something that everyone is born with, it can be learned and understood over time and practice. In this physical world, we always receive problems that are unclear and usual. As a data scientist, you should know how to translate vague and unclear problems into clear, understanding, and measurable problem statements That will help in achieving desired results for your entire project.

2- Programming skills:- Data science is revolving around in this new digital era. Technical knowledge is an integral part of data science. Some of the data scientists are required to write certain instructions to perform a set of tasks and give outcomes for further data analysis.

3- Machine learning and AI:-This field is continuously evolving and hence there is a rise in demand and importance. It is very crucial and extremely required for a data scientist to perform machine learning and AI tasks effectively as everything that a data scientist starts off is highly predictive and machine learning, AI techniques will help them in better decision making and accordingly take appropriate real-time actions without human intervention. This technology is helping in analyzing huge chunks of data through automation that performs repetitive tasks.

4- Data Visualisation and storytelling:- Data visualization and storytelling are data with a life. Data scientists are extremely talented to play around with data but data representation without visually appealing content and storytelling concepts are not sufficient to convey your message to end-users.

A good data scientist not only understands the data but also understands the business requirements and target audience. A good data scientist should have excellent storytelling skills because only a good storyteller will ensure that the result from data analysis and data modeling is conveyed to the right audience through the right channel.

5- Model Deployment:-Your end-users do not care if you have an extremely accurate model if it is not user-friendly. It is unfair for non-technical users to connect with your application or program to see how your model is performing. A good data scientist is able to deploy a model which is accessible to all users without any disconnection. The most attractive invention to achieve this is creating APIs around the model which will connect different applications into one and hence make it more feasible for end-users.