Why Management & Commerce Students Are Moving to Data Science: A New Frontier in 2025

Would you believe it if you’re told that there are better options than CA, CS, and MBA for management & commerce students? If that sounds too good to be true, then this guide is just for you. 

Data science has shown a shocking 650% job growth rate as compared to other fields, says TOI. That’s the reason why management & commerce students are moving to data science. And why not? It has everything. Promising careers, promising salaries, and stability, you name it. 

If you’re also awestruck by data science and want to become a data scientist after Bcom, then what you’re about in this guide will excite you. You’ll learn what the field is all about and how you can enter it being a commerce & management student. Let’s dive right in!

What is Data Science and Why It Matters in 2025

Data science deciphers patterns, predicts outcomes, and transforms businesses through precise insights, changing decision-making in management across industries.

Industries are using the following applications of data science. These innovations might even surprise you.

• Optimize healthcare with predictive diagnostics and real-time patient monitoring.
• Power retail with personalized recommendations that tempt even your frugal side.
• Drive finance by spotting fraud faster than scammers can blink.
• Enable smarter logistics with supply chain forecasts that even fortune tellers envy.

You might wonder why data science matters so much for commerce graduates. The following reasons show its untapped potential in your field.

• Discover trends hidden in financial data, just waiting for you to uncover.
• Master customer insights that drive your marketing campaigns from bland to bold.
• Blend business acumen with analytical skills, a combination that employers value highly.
• Unlock roles like a data scientist after BCom, bridging commerce and tech seamlessly.

Also Read: Importance of Data Science in 2025 [A Simple Guide]

Now that you know what data science is and why it is a promising field in 2025, let’s see how it’s creating a new direction for commerce & management students in the next section. 

Why Management & Commerce Students Are Moving to Data Science? A New Direction

As a management or commerce student, you're already equipped with a strong foundation in analysis, problem-solving, and business strategy. Now, imagine amplifying these strengths by diving into the world of data science. 

This emerging field offers you the chance to apply your analytical skills in new, exciting ways, unlocking career opportunities that blend business insights with cutting-edge technology. 

Let’s explore how your background positions you perfectly for this transformation.

Strong Analytical and Financial Background

Numbers tell stories, and you know how to read them. Your ability to analyze financial data and uncover trends positions you to thrive in data science.

The following examples show how your financial expertise fuels innovation in data-driven industries.

• Solve intricate financial puzzles using predictive models.
• Use statistical techniques to evaluate potential investments.
• Decode market trends to stay ahead of economic shifts.
• Analyze business metrics to guide better decision-making.

Also Read: How to Develop Analytical Thinking? [A Complete Guide]

By blending your analytical skills with data science, you unlock a new realm of opportunities. Now see how understanding business processes amplifies your potential.

Understanding of Business Processes

You’ve spent years mastering business operations. That knowledge transforms you into a valuable asset when paired with data science, where insights drive action.

These examples show how your understanding of business processes aligns with data science.

• Map out customer journeys to sharpen marketing strategies.
• Predict operational bottlenecks to improve efficiency.
• Optimize supply chains with data-backed decisions.
• Use sales trends to design dynamic pricing strategies.

This foundation sets you apart as someone who turns data into business outcomes. Now, learn how to connect technical data with business goals.

Bridging the Gap Between Data and Business

Data science isn’t just about numbers; it’s about making those numbers speak to business leaders. Your ability to connect these worlds makes you indispensable.

The following examples illustrate how you turn raw data into actionable insights that businesses can act on.

• Transform complex datasets into clear reports for decision-makers.
• Act as the translator between IT teams and executives.
• Build intuitive dashboards that simplify data analysis.
• Use predictive insights to drive strategic business moves.

Want to know more about the skills required in data science? Read: 8 Compulsory Skills You Need to Become a Data Scientist

The next step is understanding how you can transition fully into the role of a data scientist after BCom.

Can Management and Commerce Students Become a Data Scientist?

Commerce students have skills that perfectly align with data science. These strengths make transitioning into this field both achievable and rewarding.

The following insights explain why management & commerce students are moving to data science and how their expertise fits this evolving domain.

Skills Commerce Students Bring to the Table

Commerce graduates are no strangers to working with data. Their background in numbers and business strategy offers a unique advantage in data science.

Below are examples of skills that make you a strong fit for data science roles.

• Financial expertise helps in analyzing and interpreting complex datasets.
• Problem-solving skills prepare you for creating predictive models and actionable insights.
• Business acumen ensures data-driven strategies align with organizational goals.
• Experience in pattern recognition equips you to extract trends from raw data.

These qualities highlight why management & commerce students are moving to data science and excelling in the field. But what about the myths surrounding coding and math?

Debunking the Math and Coding Myth

You don’t need to be a math genius or a coding wizard to step into data science. These myths often discourage commerce students, but the truth is much simpler.

Below are reasons why these barriers aren’t as intimidating as they seem.

• Basic coding skills in Python or R are sufficient to start your journey.
• Tools like Tableau and Power BI minimize the need for advanced programming.
• Statistics you’ve already learned in your coursework cover essential concepts.
• Online resources break coding and math into manageable steps for beginners.

While advanced coding skills aren't required, having a solid understanding of the technology will make you a standout candidate for any employer. You can explore both technical and non-technical aspects of data science through upGrad's free data science courses.

This clarity helps you understand why management & commerce students are moving to data science despite these common misconceptions. Now, let’s explore the steps you can take to become a data scientist after BCom.

Steps for Management and Commerce Students to Become a Data Scientist

You can transition into data science by following a structured path. Your commerce background provides a solid foundation for this journey.

The steps below guide you through acquiring the necessary skills and experience to become a data scientist after BCom.

Step 1: Learn Data Science Basics

Building a strong foundation in data science begins with understanding key programming languages and statistical concepts.

Focus on these essential areas as you start. 

• Programming Languages: Learn Python and R, which are widely used in data science for their versatility and ease of learning.
• SQL: Master SQL to manage and query databases effectively.
• Statistics and Probability: Develop a solid grasp of statistical methods and probability theories to analyze data accurately.

Learn SQL for free with upGrad’s introduction to database design with MySQL certification course.

With these basics in place, you can move on to presenting data insights effectively.

Step 2: Master Data Visualization

Effectively communicating data findings is crucial, and data visualization tools help present complex data in an understandable manner.

Learn to use tools like these to create impactful visualizations. 

• Tableau: Create interactive and shareable dashboards.
• Power BI: Develop business analytics solutions with rich visualizations.
• Excel: Utilize advanced charting features for quick data visualization.

Looking to learn data visualization? Start with Tableau and get a hands-on experience with upGrad’s free certification course. 

Mastering these tools enables you to convey data-driven insights compellingly. Let’s explore in detail. 

Step 3: Learn Business Analytics

Your commerce background offers a unique advantage in understanding business processes. Enhancing this with analytical tools bridges the gap between data and business strategy.

Use these steps to integrate business analytics into your skill set. 

• Analytical Tools: Learn to use SAS or SPSS for sophisticated data analysis.
• Market Trend Analysis: Apply analytical methods to interpret and predict market behaviors.
• Data-Driven Decision Making: Use data insights to inform and guide business strategies.

Business analytics is key to your role, and upGrad’s professional certification course, co-designed by PwC India, offers industry-relevant expertise and practical skills. Enroll now!

This integration positions you to leverage data for strategic business decisions. Up next is machine learning. 

Step 4: Acquire Machine Learning Skills

Machine learning enables predictive analytics and automation in data science. Gaining proficiency in this area is essential for advanced data roles.

Start your machine learning journey by focusing on the following.

• Regression Models: Understand linear and logistic regression for predictive analysis.
• Classification Techniques: Learn methods like decision trees and support vector machines for categorizing data.
• Clustering Methods: Study algorithms like K-means to group similar data points.

Machine learning is a must-learn skill, there’s no debate about that. upGrad’s PG program in ML & AI by IIT Bangalore has been trusted by 10,000+ students for over 8 years. Enroll yourself today and add the skills and certifications to your resume.

Now, let’s see how you can get hands-on experience. 

Step 5: Work on Real-World Projects

Practical application of your skills is crucial. Engaging in real-world projects solidifies your learning and demonstrates your capabilities.

Gain valuable experience by exploring these opportunities.

• Internships: Seek opportunities that allow you to work on data analysis projects.
• Kaggle Competitions: Participate in data science challenges to solve real-world problems.
• Open-Source Contributions: Collaborate on projects that showcase your data science skills.

Practical experience helps you create a portfolio that stands out to potential employers.

Step 6: Build a Portfolio and Resume

A well-curated portfolio and resume highlight your skills and projects, making you stand out to employers.

Include these key elements in your portfolio.

• Diverse Projects: Showcase work across different domains to demonstrate versatility.
• Certifications: Take relevant data science courses & add certifications to validate your expertise.
• Visual Presentations: Use dashboards and case studies to present your work clearly.

A compelling portfolio paves the way for job applications. Let’s take a look at the roles. 

Step 7: Apply for Data Science Roles

With your skills and portfolio ready, begin applying for entry-level positions that suit your background.

Consider roles such as the following. 

• Data Analyst: Focus on interpreting data to inform business decisions.
• Business Analyst: Bridge the gap between IT and business teams using data insights.
• Junior Data Scientist: Engage in building models and analyzing data under supervision.

Also Read: Career in Data Science: Jobs, Salary, and Skills Required

Applying for these roles marks the beginning of your career in data science. Next, explore the top skills needed to succeed in this field.

Top Skills Needed to Succeed in Data Science

Success in this field depends on developing specific skills that set you apart. Let’s explore the most essential ones.

• Programming Skills (Python, R, SQL): Learn these versatile languages to analyze data and build models efficiently.
• Mathematical and Statistical Knowledge: Strengthen your foundation in statistics, probability, and linear algebra to understand the science behind the data.
• Business Acumen for Problem-Solving: Use your commerce background to identify and solve real-world business problems with data.
• Data Wrangling and Preprocessing Techniques: Clean and organize raw data to make it usable for analysis.
• Communication and Storytelling with Data: Present insights in a way that captivates and informs decision-makers.

Also Read: Learn Data Science – An Ultimate Guide to become Data Scientist

Now that you know the top skills for success, it’s time to focus on the unique skills commerce graduates bring to the table.

Skills Required to Become Data Scientist After B.Com

Explore these essential skills that can help you transition into data science.

• Understanding of Financial Data: Analyze and interpret complex financial datasets with confidence.
• Proficiency in Excel: Use advanced Excel features for data analysis and visualization.
• Market Trend Analysis: Leverage your knowledge of market dynamics to uncover actionable insights.
• Report Writing and Presentation: Create professional reports that translate data into clear business recommendations.
• Learning Adaptability: Embrace new tools and techniques to stay relevant in this evolving field.

By building on these skills, you can position yourself as a capable data scientist after BCom. Now, let’s address the challenges you might encounter and how to overcome them.

Challenges Management and Commerce Students May Face (And How to Overcome Them)

Switching to data science from a commerce or management background is exciting but not without hurdles. You may face obstacles that seem daunting but can be overcome with the right approach.

These challenges may feel familiar, but they’re manageable when broken down into actionable steps.

• Limited Coding Knowledge: As a commerce graduate, coding may feel intimidating. Start small with Python and SQL, using beginner-friendly platforms and tutorials. Practice regularly to build confidence.
• Tackling Mathematical Concepts: Advanced math might seem overwhelming, but your existing knowledge of statistics gives you a solid start. Focus on practical applications of math in data science rather than theory.
• Competing with Tech Graduates: You bring unique business insights that tech graduates often lack. Highlight your ability to connect data with business strategies to stand out in the field.

Now, let’s look at the career paths you can pursue after gaining expertise in data science.

Career Paths for Management and Commerce Students after Data Science

Data science unlocks diverse career opportunities for you, blending your business insights with technical skills. These roles value the combination of analytical expertise and commerce-driven understanding.

The following table showcases some of the most rewarding roles for you as a data scientist after BCom.

Source: Glassdoor

Also Read: Top 15 Jobs for Data Science Highest Salary in India 2025

These roles show why management and commerce students are moving to data science and thriving in it. Now, let’s explore how upGrad can help you prepare for this transition.

How Can upGrad Help You?

upGrad is a leading online learning platform with over 10 million learners, offering 200+ courses and partnering with 1,400+ hiring companies. We provide comprehensive programs tailored to equip you with the skills needed to become a data scientist after BCom.

Here are some of the top courses from upGrad, designed to suit your learning needs: 

• Master’s Degree in Artificial Intelligence and Data Science
• Post Graduate Programme in Data Science & AI (Executive)
• Post Graduate Certificate in Data Science & AI (Executive)
• Professional Certificate Program in Business Analytics & Consulting in association with PwC India
• Free Data Science Courses Galore

To support your learning journey, we offer free one-on-one expert consultations. Our experienced counselors provide personalized guidance to help you choose the right course and career path. Additionally, with 29 offline centers across India, you have access to in-person support and resources to enhance your educational experience.

Unlock the power of data with our popular Data Science courses, designed to make you proficient in analytics, machine learning, and big data!

Elevate your career by learning essential Data Science skills such as statistical modeling, big data processing, predictive analytics, and SQL!

Stay informed and inspired with our popular Data Science articles, offering expert insights, trends, and practical tips for aspiring data professionals!

Reference: 
https://timesofindia.indiatimes.com/blogs/voices/data-science-a-bankable-career-path-for-indian-youth/
https://www.glassdoor.co.in/Salaries/data-analyst-salary-SRCH_KO0,12.htm
https://www.glassdoor.co.in/Salaries/business-analyst-salary-SRCH_KO0,16.htm
https://www.glassdoor.co.in/Salaries/junior-data-scientist-salary-SRCH_KO0,21.htm
https://www.glassdoor.co.in/Salaries/risk-analyst-salary-SRCH_KO0,12.htm
https://www.glassdoor.co.in/Salaries/financial-data-analyst-salary-SRCH_KO0,22.htm