Junior Data Scientist: Gen AI & ML in Production

Monetary Authority of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Monetary Authority of Singapore (MAS) is seeking a fresh graduate for its Data Analytics & Engineering Division. You will explore generative AI, build ML-powered web apps, and collaborate across teams to turn data insights into business value.

Ideal candidates have a degree in Data Science or Computer Science, Python proficiency, and a foundation in statistics and cloud concepts. The role emphasizes Agile methods, rapid delivery, and learning new technologies in a dynamic environment.

Qualifications

• Fresh graduates with relevant degrees are welcome to apply.
• Proficiency in Python and ML techniques required.
• Strong statistical analysis and teamwork skills.

Responsibilities

• Explore, utilise, and implement generative AI technologies to solve challenges and deliver business value.
• Build ML-enabled web applications, transitioning from PoC to production.
• Develop ML models for classification, regression, clustering, and forecasting.
• Conduct data analysis to derive actionable insights for business problems.
• Apply statistics to interpret distributions and derive significant metrics.
• Collaborate with cross-functional teams using Agile to deliver improvements.
• Analyse requirements, recommend solutions, contribute to cloud app implementation.

Skills

Python

ML techniques

Statistical analysis

Agile basics

Business analysis

Communication

Project management

Willingness to learn

Education

Data Science

Computer Science

Tools

Open-source libraries

Job description

Monetary Authority of Singapore (MAS) is seeking a fresh graduate for its Data Analytics & Engineering Division. You will explore generative AI, build ML-powered web apps, and collaborate across teams to turn data insights into business value.

Ideal candidates have a degree in Data Science or Computer Science, Python proficiency, and a foundation in statistics and cloud concepts. The role emphasizes Agile methods, rapid delivery, and learning new technologies in a dynamic environment.