Data Scientist

Data Scientists make use of analytical, statistical, and programming skills to collect, analyse, and interpret large data sets. This information is used to develop data-driven solutions to solve difficult business problems.

Data Scientist Job Description

Clean and organise data to be used for analysis.
Develop data visualisations to effectively present insights and stories to the stakeholders.
Identify new business questions that will value-add.
Develop new analytical methods and machine learning models for the client.
Monitor and ensure the business model’s remains aligned with the business goals.

Note

Singapore’s GovTech used a data science approach to find the problematic MRT train that was responsible for the series of breakdowns!

A day in the life

Data Scientist

Data Science is not just about picking out trends and insights from statistics and other data. Find out what it takes to be a Data Scientist at URA.

What you should know about Data Scientist jobs in Singapore

Nature of work

As Data Scientists, you will engage in data analysis to extract meaningful insights from complex datasets using machine learning and predictive modelling.

Key advice

You need to be good at Advanced Maths to understand various algorithms and design better models based on your knowledge.

Entry Requirements

Entry Requirements
A bachelor's degree in Statistics, Mathematics, Computer Science or related fields is preferred.

Lots of textbook learning on machine learning algorithms! As a Data Scientist, you will need to know and understand what algorithms to use to adapt the models to suit your needs.

Gain work experience - try to get internships or part-time jobs.
Possible Pathway

Possible Pathway

Skills you need to pursue a Data Scientist career in Singapore

Hard Skills

Machine Learning Skills

Design and implement machine learning models to analyse complex datasets and predict trends.

Programming Languages

Use Python, R, or Java for data manipulation, statistical analysis, and algorithm development.

Business Innovation

Leverage data insights to drive business growth and innovation.

Project Management

Plan, execute, and lead data science projects, ensuring they meet deadlines, budgets, and objectives.

Deep Learning

Knowledge of deep learning frameworks like TensorFlow or PyTorch for more advanced AI projects.

Soft Skills

Problem-Solving

Identify, analyse, and solve complex problems using data-driven approaches.

Patience

Persistence and resilience in working through complex data analysis processes and research.

Critical Thinking

Ability to critically evaluate data, methodologies, and results to ensure accuracy and relevance.

Leadership

Lead teams, make decisions, and inspire others in the pursuit of data-driven objectives.

Transdisciplinary Thinking

Combine knowledge from different disciplines to enhance data analysis and interpretation.

“Don't see errors as failures, be positive. These are important lessons to help you improve over time.”

Songyu, Data Scientist

Frequently asked questions (FAQs)

What is the difference between Data Scientists and Data Analysts?

Data Scientists estimate the unknown, while Data Analysts explore known data from new perspectives. Their responsibilities can overlap depending on the workplace.
Are Data Scientist positions in demand in Singapore?

Data Scientist roles are in high demand in Singapore as companies continue to store and process increasing amounts of data.
Do Data Scientists need to learn a programming language?

Yes. Programming skills are essential as Data Scientists need to write code, typically in Python or R, to analyse data, build machine learning models and create data visualisations.
What software do Data Scientists use for their job?

Some of the most commonly used software by Data Scientists are Python, Structured Query Language (SQL), R and Jupyter Notebook.
How do Data Scientists ensure they have found the most optimal solution to solve a problem?

Data Science is an iterative process, and they continuously iterate and refine models based on feedback and new insights to ensure optimal solutions.