How to Build a Career in Data Science? [2025]

Introduction

Data Science is one of the most thriving fields of work in the current technologically-driven world. From Sports to Entertainment to Medicine to Hospitality, every field desires and demands Data Science professionals for their expert data-driven opinions. This helps them make informed decisions that will directly impact their business or work positively.

A Data Science career is probably one of the most in-demand jobs right now. To pursue a career in Data Science in India, one needs to get a bachelor’s degree, preferably in a related field like Data Science, Computer Science, or Statistics. Post that, pursuing an MBA in Data Science and Artificial Intelligence, especially from colleges like MBA ESG, will go a long way into a professional’s career.

Moreover, acquiring skills in programming languages of R, Python, SQL, and SaaS, and improving Data Science skills will always benefit any professional in this line. Networking and Internships are also an add-on to one’s resume.

What is a Data Scientist?

A Data Scientist studies large sets of data to extract valuable information from it, which he/she then transforms into insightful models. This is done to solve a problem that arose out of a business need. They develop various strategies required to tackle any problem which helps both small and large businesses. They interpret data from a variety of fields like Mathematics, Statistics, Business, Computer Science, etc.

Data Scientists generally collect data, analyze, and interpret such data, before predicting patterns and trends that give them insights to create a model that is good for business-related decisions.

Data Scientists use their skills in programming, statistics, and industry domains to reach a solution.

The Data Science Career Path: Skills Required for Data Scientists

The entirety of a Data Scientist’s skillset and their mode of operation can be broken down into a 6-step process. They are as follows:

1. Understanding the Problem

A Data Scientist must first and foremost understand the nature of the problem and even enquire about it from their client. Without understanding the nature and root of the problem, a Data Scientist cannot start collecting the right data to analyze and interpret.

2. Data Gathering

Data Scientists must then try and gather as much relevant data as possible. They have multiple sources to collect them from such as Web Servers, Logs, Databases, APIs, Online Repositories, etc.

3. Data Refining

Data Refining is done in a two-step method: First comes Data Cleaning, which is filtering the right information from the wrong ones such as misspellings, missing information, and inconsistency. Then comes Transforming or Modifying the data as per mapping rules. Tools like Talend and Informatica help in this case.

4. Exploratory Data Analysis

This step is just to further refine the data into a purer subset before choosing a variable to create a model.

5. Data Modelling

Here, machine learning techniques like KNN, Decision Tree, and Naive Byes, are applied to predict the correct model for the data set. Platforms where such data can be modelled are R, Python, and SaaS.

6. Deployment and Maintenance

Finally, a Data Scientist deploys the correct model and maintains its quality by further enquiring to the clients if their problem is solved.

Some of the other skills that Data Scientists require are:

Data Visualization, Statistical Analysis, Machine Learning, Artificial Intelligence, Deep Learning, Natural Language Processing, Big Data, and Cloud Computing.

Building a Career in Data Science: Data Science Job Roles

Studying Data Science as a career in it can open up many roles and designations that are both lucrative and passion-filled experiences. Here are some of the job roles in Data Science:

1. Data Analyst

They collect, clean, and analyze data before providing information on the same.

2. Data Engineer

They build, design, and maintain systems and architecture for data storage and generation.

3. Junior Data Scientist

Model building, Experimentation, and basic data analysis tasks are part of their job role.

4. Data Scientist

They develop algorithms to solve business problems, predict the solution model, and analyze in-depth data.

5. Machine Learning Engineer

They design, implement, and deploy machine learning models at the required scale.

6. Data Product Manager

The data-driven products and features are managed by them.

7. Senior Data Scientist

They provide strategic guidance and lead complex data science projects.

Risk Analyst, Business Analyst Manager, Supply Chain Analyst, Data Manager, Customer Insights Analyst, etc., are some of the other Data Science career opportunities one can pursue.

Building a Career in Data Science: The Data Scientist Job Market

The Harvard Business Review called Data Science “The Sexiest Job of the 21st Century.” A Data Science career for freshers is like being a part mathematician, part computer scientist, and part trendsetter.  It is very high in demand. An MBA in Data Science & AI is sought after role among Top Management.

Market trends show that the Data Science market was valued at $96.3 billion in 2022, and is expected to reach around $378.7 billion by 2030. The compound annual growth rate (CAGR) is 16.43% from 2023 to 2030. By 2033, the value of the market will more than double itself, taking the growth to 36% from 2023 to 2033.

Some of the reasons behind this rapid growth of the Data Science market are:

  • Data will be an even more imperative measure in every walk of life, which will fuel the demand for it even more.
  • Higher Salaries – Senior Data Scientists can earn up to or more than 40 LPA currently. This figure is predicted to rise even further, which will drive its demand to a crazy limit.
  • Transferable Skills – Learning Data Science skills can be applied to many different fields of work. Hence, more people will want to pursue it.
  • Its Ubiquitous Nature in All Industries – From Healthcare to Entertainment to Hospitality to Sports to Security to many other walks of life, Data Science will be important everywhere.

The Future of Data Science: Is Data Science a Good Career?

As mentioned above, Data Science is possibly going to be (maybe already is) one of the most highly demanding jobs shortly. It provides a sense of accomplishment to those who love working with data since it’s their passion turned dream come true.

The salaries are high enough in this work for anybody to jump on the bandwagon of pursuing Data Science. More importantly, due to the impactful nature of Data Science and its penetrability in every field, employees working with Data Science will feel like they have made a difference.

Take a Sports Analyst for example, who will get the job after studying Data Science. He/She will provide real-time insights into an athlete’s performance, endurance, strengths, weaknesses, and other aspects, only to be applied immediately. This will make a tremendous difference to their game.

Besides huge earning potential and a variety of career opportunities, a Data Scientist will also work with cutting-edge technologies. There is a rising demand for even specialized professionals in this field of work. Lastly, the continual rise of AI will also heavily tilt the favor towards Data Science in the future.

Frequently Asked Questions

1. What is a Data Science Career?

A Data Science career is one where an employee works with a particular data set to extract valuable insight from it, to provide a solution to a problem. It is the most in-demand job at the moment and it is also a very highly paid job with salaries reaching up to INR 40 LPA.

2. How to Start a Career in Data Science?

To start a career in Data Science, one must pursue a Bachelor’s Degree, preferably in the field of Data Science or Computer Applications. Post that, they can pursue an MBA in Data Science and Artificial Intelligence, especially from a college like MBA ESG. Acquiring skills like R, Python, SQL, and SaaS, and doing internships and projects, go a long way in this career.

3. Is Data Science a Good Career?

Yes. Data Science is a good and thriving career option. With the rise of AI and various technological advancements, Data Science has become a prosperous career option. An MBA professionals can earn up to INR 35-40 LPA with experience.

4. How is the Career in Data Science?

A career after Data Science is very lucrative and very appealing. It has high-paying jobs up to INR 30-40 LPA for senior positions, and it has relevance and existence in almost all fields of life i.e. Entertainment, Hospitality, Healthcare, Space, Sports, etc. There are multiple options for an employee to pursue a career in Data Science.