Data science has rapidly become one of the most sought-after and rewarding careers in Singapore. In 2024, salaries for data scientists surged by 11.3% year-on-year, outpacing many other tech roles and signaling strong demand across industries, from finance to healthcare to AI startups. For those aspiring to enter this profession, understanding the essential data scientist requirements is crucial.
This blog will give you a detailed overview of how to become a data scientist and will walk you through every step to launch your data science career in Singapore’s booming tech landscape.
Also Read: How to Earn Passive Income as a Data Scientist in Singapore?
Steps to Become a Data Scientist
Embarking on a career in data science can seem daunting, but with the right approach, anyone can break into this in-demand field. Here’s a clear roadmap for beginners exploring how to be a data scientist.
Step 1: Understand the Role
Before diving in, it’s crucial to learn what data scientists do. They collect, process, and analyze vast amounts of data to help businesses make data-driven decisions. Understanding this role sets the foundation for all future learning and skills.
Step 2: Build a Strong Educational Foundation
Most data scientists have a background in computer science, mathematics, or engineering. But if you’re self-taught, online degrees and bootcamps are also effective. This is an important first step in figuring out how to learn data science.
Also Read: Is a Master’s in Data Science worth it for a Career Switch in Singapore?
Step 3: Develop Technical and Analytical Skills
Being technically sound is non-negotiable. Learn programming languages like Python and R, work with databases using SQL, and master tools like Excel and Tableau. These are core data scientist requirements for any entry-level role.
Step 4: Master Mathematics and Statistics
A strong grasp of statistics, probability, and linear algebra is essential. These concepts help you build models, test hypotheses, and analyze results. Without these, your ability to interpret data accurately will be limited.
Step 5: Work on Projects and Build a Portfolio
Apply your knowledge by working on real-world datasets and uploading your projects to GitHub or Kaggle. This helps you stand out when exploring how to start a career in data science, showing employers you can apply theory to practice.
Step 6: Earn Relevant Certifications
Certifications in data science, machine learning, or cloud platforms can strengthen your resume. They prove you’re serious about your career and meet the professional data scientist requirements that employers look for.
Step 7: Network, Prepare, and Apply
Join LinkedIn groups, attend data science meetups, and connect with mentors in the field. Networking is a powerful way to understand how to be a data scientist in today’s competitive market and land your first role.
Also Read: Top Data Science Tools Every Singapore Professional Should Learn
Career Path and Opportunities in Data Science
Explore the dynamic career progression in data science, from foundational roles to advanced specializations. Here’s a quick overview:
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Also Read: Data Scientist Demand in Singapore: Top Companies Hiring in 2025
Advancing Your Data Science Career with upGrad
upGrad’s tailored online data science programs are designed to fast-track your career with a blend of academic rigor and industry relevance. Learn from top global universities, gain hands-on experience through real-world projects, and benefit from 1:1 mentorship by industry experts. upGrad’s strong employer network and career support services ensure you’re job-ready, making it the ideal platform to advance your data science journey with confidence and credibility.
Explore these online data science courses through upGrad!
- Master of Science in Data Science (Liverpool John Moores University)
- Executive Diploma in Data Science and AI (IIT Bangalore)
- Post Graduate Certificate in Data Science and AI -Executive (IIT Bangalore)
FAQ on How To Become A Data Scientist
Q: What educational background is required to become a data scientist?
Ans: A strong foundation in mathematics, statistics, and computer science is the ideal educational background to become a data scientist. Most data scientists hold degrees in fields like Computer Science, Engineering, Mathematics, or Data Science.
Q: Which programming languages should I learn for data science?
Ans: Python and R are the most popular programming languages for data science. Additionally, knowledge of SQL for database handling and familiarity with tools like MATLAB, Scala, or Julia can be beneficial.
Q: What industries hire data scientists?
Ans: Data scientists are in demand across diverse industries, including finance, healthcare, e-commerce, technology, manufacturing, education, and even government sectors.
Q: How long does it take to become a data scientist?
Ans: It typically takes 6 months to 2 years, depending on your prior experience, learning path, and consistency. Structured programs and hands-on projects can accelerate your journey.
Q: How can upGrad help me in my data science journey?
Ans: upGrad offers industry-relevant data science programs in collaboration with top global universities. With expert mentorship, real-world projects, and 24/7 support, learners can build strong portfolios and transition smoothly into data science careers.
