upGrad Singapore
  • MBA
  • Data Science & Analytics
  • Machine Learning & AI
  • Doctorate of Business Administration
  • More
    • Coding & Blockchain
    • Management
    • Product and Project Management
    • General
    • Digital Marketing
    • Law
    • Education
No Result
View All Result
  • MBA
  • Data Science & Analytics
  • Machine Learning & AI
  • Doctorate of Business Administration
  • More
    • Coding & Blockchain
    • Management
    • Product and Project Management
    • General
    • Digital Marketing
    • Law
    • Education
No Result
View All Result
upGrad Singapore
Home Singapore Blog Data Science & Analytics Top Data Scientist Interview Questions in Singapore (2025 Guide)

Top Data Scientist Interview Questions in Singapore (2025 Guide)

Rohit Sharma by Rohit Sharma
October 8, 2025
in Data Science & Analytics
Top Data Scientist Interview Qs
Share on TwitterShare on Facebook

The top companies hiring data scientists in Singapore conduct extensive interviews before finalising candidates. The common interview questions are designed to assess your basic knowledge as well as your advanced technical skills.
As a data scientist working in Singapore, you can earn an average annual salary of SGD 8,250 per year.
Explore common data scientist interview questions and their respective answers, and be prepared to stand out in the highly competitive arena.

Also Read: Best Programming Languages for Data Science in 2025

Top Data Scientist Interview Questions and Sample Answers

If you’re currently preparing for data science roles in Singapore, make sure you’re going through the list of common interview questions and sample answers, shared below.

Common Interview Questions and Sample Answers

Here’s a look at the top common interview questions and answers: 

1. What is Data Science?

Data science involves the deployment of programming, statistics, and domain expertise to extract meaningful insights from a massive volume of available data.

2. Explain the difference between supervised and unsupervised learning.

Supervised learning, usually used for classification tasks, focuses on input-output pairs. Unsupervised learning, on the other hand, identifies groupings or patterns without predefined labels.

3. What is overfitting, and how can it be prevented?

Overfitting occurs when a data model ends up memorising training data too closely and offers generalised answers based on that memory.

4. How do you handle missing or corrupted data in a dataset?

The method of handling missing data involves identifying the reason behind the missing data and then deploying imputation, deletion, or flagging.

5. Describe a time when you explained a complex data science concept to a non-technical stakeholder.

This one remains one of the common questions they ask in an interview. Answers may vary widely based on individual experiences. We have shared an example below.

I once helped business leads grasp model accuracy by translating accuracy metrics, analogies, and visuals, such as graphs and charts.

Also Read: Data Scientist Demand in Singapore: Top Companies Hiring in 2025

6. What is cross-validation, and why is it important?

Cross-validation is a key step in model evaluation. It helps evaluate generalising tendencies of models by testing them on different data subsets, thereby preventing inaccuracies like overfitting.

7. How do you ensure your models are not biased?

I usually start by examining data sources and their representation, evaluating model performance across groups, and performing audits on a regular basis to ensure fairness.

8. Can you walk me through a data project you worked on from start to finish?

For a campaign optimisation project at my previous company, I gathered user data, engineered relevant features, built and tuned a logistic regression model, and then deployed it to production.

9. What are the most essential data visualisation techniques, and when would you use them?

Bar plots are best suited for comparing categories, such as revenue or market share, while line plots help visualize trends over time. Histograms reveal how numeric data is distributed.

10. How do you select the correct algorithm for a data science project?

Choosing an algorithm begins with understanding the problem—whether it involves classification, regression, or clustering—and evaluating the structure and size of the dataset.

Also Read: Data Science vs. Machine Learning Engineer

Common Behavioural and Technical Questions in Data Science Interviews 

Besides the general interview questions listed above, be prepared to ace the common behavioural and technical questions as well.

Here’s a quick look at the top behavioral and technical interview questions for data scientists in Singapore:

Questions

Sample Answers

How do you deal with messy data sets?Messy data sets can be fixed by removing unwanted data sets and fixing structural errors
How do you handle data quality issues?Through the implementation of robust data validation and monitoring processes
How do you ensure the right balance of speed and accuracy while deploying machine learning models?It can be done through selecting the correct algorithms and optimising training processes
What is logistic regression?It’s deployed in supervised machine learning for classification problems
What is a linear model? What are its drawbacks?It’s a linear mathematical representation of variables susceptible to overfitting.
LJMUMSD

How upGrad Empowers Singapore Students for Data Science Careers

Strengthen your data science interview preparation by enrolling in one of the Data Science & Analytics courses offered by upGrad. The duration of these Master’s and Diploma courses varies from 6 to 18 months, offering facilities such as online learning and specialisations in preferred domains:

Explore these online courses through upGrad!

  • MS in Data Science from Liverpool John Moores University
  • Executive Diploma in Data Science and AI
  • Executive Post Graduate Certificate Programme in Data Science

FAQ on Data Scientist Interview Questions in Singapore

Q: What are the key skills required for a data scientist role?
Ans: Programming, data wrangling, database management, statistics and probability, and machine learning and deep learning are the top skills every data scientist should have.

Q: What programming languages are essential for data science?
Ans: Python, R, SQL, Java, and Julia are a few programming languages essential for data science. There are several hundred programming languages out there – some of which suit the specifics of your role as a data scientist better than other.

Q: What industries in Singapore are hiring data scientists?
Ans: Science and Technology, information and communication technology, banking and financial services, Digital Marketing, and Healthcare are among the top industries hiring data scientists in Singapore.

Q: How does upGrad support career transitions into data science?
Ans: upGrad supports career transitions in data science through its comprehensive data science courses, which focus on developing both behavioural and technical attributes, its strong network of recruiters, and unparalleled career guidance.

Q: Which companies in Singapore are hiring data scientists?
Ans: Some of the well-known companies currently hiring data scientists in Singapore are Moloco Singapore PTE Limited, Marina Bay Sands, Alexandra Hospital, Airwallex, and Yokogawa Engineering Asia PTE Ltd, among others.

Rohit Sharma

Rohit Sharma

42 articles published

Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Previous Post

Top 10 Employee Benefits Offered by Leading Employers in Singapore

Next Post

Pursuing an MBA in Healthcare in Singapore: Is It the Right Path for You?

  • Trending
  • Latest
What Does a Product Development Manager Do?

Role of a New Product Development Manager: Key Roles and Responsibilities

October 15, 2025
Advanced Neural Networks: Theory to Real

Advanced Neural Networks: From Theory to Practice

September 4, 2025
Statistical Tools in Research

Statistical Tools Used in Research Methodology: A Comprehensive Guide

September 19, 2025
Ed.D. in Organizational Leadership Salary Expectations and Career Paths

Ed.D. in Organizational Leadership: Salary Expectations and Career Paths

October 23, 2025
AI Engineer Salary in Singapore Trends, Skills & Career Outlook

AI Engineer Salary in Singapore: Trends, Skills & Career Outlook

October 24, 2025
Power BI vs. Tableau Which Tool Do Singapore Companies Prefer

Power BI vs. Tableau: Which Tool Do Singapore Companies Prefer?

October 14, 2025

Get Free Consultation

upgradlogo.png

Building Careers of Tomorrow

Get the Android App
apple [#173]Created with Sketch. Get the iOS App
Upgrad
  • About
  • Careers
  • Blog
  • Success Stories
  • Online Power Learning
  • For Business
  • upGrad Institute
Support
  • Contact
  • Terms & Conditions
  • Privacy Policy
  • Referral Policy
Browse Courses by Region
  • Courses in Singapore
  • Courses in the UAE
  • Courses in the US
  • Courses in Canada
  • Courses in Australia
  • Courses in Saudi Arabia
  • Courses in the UK
  • Courses in Vietnam
Popular Posts
  • Ed.D. in Organizational Leadership: Salary Expectations and Career Paths
  • AI Engineer Salary in Singapore: Trends, Skills & Career Outlook
  • Power BI vs. Tableau: Which Tool Do Singapore Companies Prefer?
  • Most In-Demand Tech Jobs in Singapore: What Employers Are Looking For
  • Top Career Opportunities in Python for Singapore Professionals in 2025-26

KEEP UPSKILLING WITH UPGRAD

Ushering the Era of Learning and Innovation
Back in 2015, upGrad’s founders noticed that the future of work demands industry professionals to upskill continuously – not just for their organization’s benefit but also for their personal growth. Earlier, learning would come to a halt as soon as professionals entered the workspace. upGrad brought along novel approaches towards imparting and receiving education by offering people a chance to upskill while working. We have always strived to facilitate quality education to the upcoming workforce through industry-relevant UG and PG programs.

Staying Dynamic and Forward-Looking
From being incepted in 2015 to teaching a learner base of 10k+ in 2018 to crossing the 1M mark in 2020 – upGrad has always focused on staying dynamic and future-centric. This approach has helped us grow as an organization while catering best-in-class learning to our students. In 2021, upGrad became a unicorn with a valuation of $1.2B, expanding to North America, Europe, the Middle East, and the Asia Pacific. Only onwards and upwards from here!

Growing and Expanding Constantly
Growth has been our true constant in this journey. Whether it is entering the unicorn club or winning the Best Career Planning platform award, or being ranked the #1 startup in India per LinkedIn’s 2020 report – we’ve always strived to go above and beyond our current capacities and bring novel ideas to the table for the betterment of learners across the globe. Join us in this revolution and help us impact more lives!

© 2015-2025 upGrad Education Private Limited. All rights reserved  

No Result
View All Result
  • MBA
  • Data Science & Analytics
  • Machine Learning & AI
  • Doctorate of Business Administration
  • More
    • Coding & Blockchain
    • Management
    • Product and Project Management
    • General
    • Digital Marketing
    • Law
    • Education