Who is a data scientist??

When someone claims to be a data scientist, it appears cool.

wow!! Data Scientist !!

A person uses various mathematical (Statistical) modelling techniques on unprocessed data to obtain information. Data scientists are known as mathematicians.

A person who develops models using programming (Python, R, SAS, etc). They are referred to as software programmers and data scientists.

THE JOURNEY:

A decade ago, they were virtually unknown, but overnight, data scientists, who work only with data and create visually appealing content from it, became popular in those companies.

They are the detached element of firms that now think about data; they are data wizard wranglers. They are the main players whose modeling skills increase the company's income.

The position of data scientist has been defined as "half analyst, part artist."

A data scientist is someone curious, who can pore through data and can see patterns. It's almost like a Renaissance person who genuinely wants to learn and alter a company.

A data scientist will most likely investigate and analyse data from many different sources, as opposed to a standard data analyst who might only look at data from one source, such as a CRM system.

The data scientist will sort through all incoming data to unearth a previously undiscovered insight that might provide them with a competitive edge or solve a critical business issue.

Data scientists do more than just gather and report on data; they also examine it from a variety of perspectives, analyse what it means, and then suggest applications for the data.

HOW IS THE ENVIRONMENT?

In all industries (banking, automotive, IT, healthcare, retail, etc.) and at all sizes of businesses (from start-ups to multinational organisations and more), data scientists work mostly in office settings, therefore there is a wide variety of work environments and cultures. Many of the nation's data scientists work in the major tech centres of Silicon Valley, New York, Seattle, and Boston, but in the competition for top talent, data scientists are frequently given the option of working remotely.

A DAY IN THE LIFE OF A DATA SCIENTIST:

• Gather Raw Data for Analysis of the Defined Problem.

• Decide on an Approach to Solve the Data Science Problem.

A data science topic may be approached using a variety of algorithmic techniques. A few of these are given below:

1. Two-Class Classification Approach.

2. Multi-Class Classification Approach.

3. Reinforcement Learning Algorithms.

4. Regression.

5. Clustering.

• Perform in-depth Data Analysis – Apply Statistical Modelling, Algorithms, and Machine Learning.

• Communicate Insights to the Stakeholders.

SKILLS:

The two biggest skills a successful data scientist needs are:

1. The ability to understand, break down, and solve complex problems with code

2. The ability to use data to tell a compelling story