A Career In Data Science

A Career in Data Science

A career in Data Science is no doubt lucrative, but you must go for it only if you have the aptitude and enjoy working on complex problems. You must be very sure a career in data science is right for you before deciding on taking up one. This article will provide you with information on data science, its techniques, different data science jobs, top data science companies, and other necessary details to decide on a data science career wisely.

What do you Understand About Data Science?

Data science is the process of preparing huge volumes of accumulated data for analysis. This process requires cleansing and aggregating the data before it is sent for analysis. The process of analysis requires analytics, algorithms, and AI models to be developed and utilised. It is software-driven and combs out the data to glean the patterns that are available, and can be used in making predictions that reveal future trends and enables organisations and businesses in better decision making. The organisations can also, through experiments, and scientifically designed tests, check the accuracy and reliability of these predictions. The data visualisation tools are used to share these decisions for everyone to clearly see and understand the pattern.

Key Components of Data Science

By combining artificial intelligence, statistics, data analysis, and scientific methods, data scientists extract relevant and important data to help businesses and organisations in their future decision-making. Data science has the following key components.

Step 1: Exploring the data

Step 2: Data Modelling

Step 3: Testing the Data Models

Step 4: Deploying Models

Process of Data Science

The different stages of the data science process are mentioned below:

  • Stage I: Identification of Problem
  • Stage II: Collection of Data for the Problem
  • Stage III: Processing of data
  • Stage IV: Exploring the Data
  • Stage V: Performing thorough Analysis
  • Stage VI: Finding the result of the analysis

Techniques of Data Science

The data science techniques are given below:

Classification Analysis

Classification analysis identifies and categorises data for analysis. Due to this, the data analysis is more accurate. In this process, classification algorithms are built with the target variable as classes. In this method, mathematical techniques like statistics, linear programming, neural network, and decision tree are used.


In data science, personalization makes use of technologies such as hyper-personalization systems and recommendation engines to match the data from the detailed profiles of individuals. This is done in order to help websites cater to the needs and preferences of individuals.

Jackknife Regression

Under this technique, the data scientists estimate the bias and variance of a selected population. It is one of the earliest methods of resampling.

Game Theory

Game theory techniques used with data science and analytics result in more accurate predictions and outcomes for decision-making. Adopting game theory helps the data scientist to predict how rational people will react and make decisions in given situations.

Decision Tree

A decision tree is used to predict on the basis of previously answered questions. It may not provide a clear decision. The Decision tree techniques provide the data scientists with options to make a decision.


Segmented data helps with marketing. It provides a better understanding of customers and the outcome of an advertising campaign. It helps the businesses cover the specific needs of different segments of the audience, and approach them accordingly.

Data Science Implementation

Due to the advances in technology, a large amount of data is continuously being generated. To make this data meaningful/ useful, it requires to be identified, organised, analysed, and interpreted in order to acquire a relevant final result. The data is analysed to spot certain patterns and trends which help the data scientists to make predictions regarding likely outcomes in the future. The organisations and businesses armed with this knowledge are able to see a lucid picture of their future. This enables them to form policies and accurate decision-making. The data is then kept in the databases for future reference. Today, businesses are becoming aware of the need for data scientists and data science implementation. Data science is emerging as a very lucrative career option. Realising this, many Institutions and online learning platforms are offering data science courses. Both professionals and fresh learners can avail of Great Learning data science online courses to progress in their careers.

Deciding on a Data Science Course

Before deciding on a Data Science course/ program, you must go through the following points thoroughly.

  • Get an idea of the responsibilities and duties of a Data Science professional.
  • You must be very certain about the job/ role you wish to pursue. There are various jobs that come under the Data Science
  •  department.
  • Evaluate if learning data science will add value to your current skills.
  • Find out about the different data science courses/ programs provided by Institutes, Universities, and online learning platforms.
  • Plan your budget accordingly.
  • Also, decide the time you will put into this.
  • Get in touch with people who have already taken the course. Take their guidance on pursuing the same.
  • Check if the chosen course/ program provides the foundational understanding of Statistics and data science.
  • Make sure that the course/ program is certified.

Data Science Jobs

Some of the data science jobs are given below:

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Mining Engineer
  • Data Architect
  • Data Statistician
  • Project Manager

Top Data Science Companies in 2022

In the current scenario of fast advancing technology, data science has emerged as a necessity for businesses and organisations. There are several opportunities available for data science professionals. The top data science companies are:

  • MuSigma
  • Fractal Analytics
  • Tiger Analytics
  • LatentView
  • Bridgei2i Analytics
  • Absolutdata
  • Teradata
  • TEG Analytics
  • Innovaccer
  • Impact Analytics



Today data has become a decision-making component, and the demand for data science professionals is also increasing. The need to harness data and glean the utmost out of it has become the objective of data science professionals. With the enormous mounds of data being produced every day, professionals in data science are in constant demand. It is a very lucrative career option, and the possibilities are endless. To help enhance your skills and improve your career prospects, you can also check out the Great Learning data science certification course online. Also, you can go through the other professional data science online courses available on the website and choose the one which will suit you best.