Data Scientist (DSAD)

4h4 hours ago

The Singapore Public Service

Singapore, SG · Full-time · S$70,000 – S$90,000

About this role

This role is an opportunity to join the Data Science and AI Division (DSAD) as an individual contributor, applying advanced analytics and machine learning to unlock the value of organizational data. Your work will deliver scalable insights that inform strategy and operational efficiency, contributing to a data-driven culture that enables smarter decision-making across the organization.

Day-to-day, you will work closely with business teams to understand their data needs, developing predictive models, dashboards, and other analytical products. You will help ensure data integrity by assessing and validating data quality, identifying anomalies, and collaborating with data engineers to resolve issues. You will apply a range of analytical approaches—from descriptive analytics to advanced machine learning—to build models for risk scoring, fraud detection, and regulatory reporting.

You will translate analytical findings into clear visualizations and actionable recommendations for both business teams and leadership. As a champion of data literacy, you will promote good data practices across the organization, helping to build a culture that values data as a strategic asset.

Successful candidates will be offered a 1-year contract with potential for a 1-year extension and consideration for permanent tenure thereafter. This role provides real impact—from building models that detect fraud and protect citizens to generating insights that shape policy and regulatory decisions.

Requirements

Proficient in statistical analysis, machine learning, and predictive modelling, with hands-on experience in Python, R, SQL, Spark, and data visualisation platforms like Tableau or Power BI.
Has some experience building machine learning models at scale, including models for risk scoring or fraud detection.
Has some exposure to deploying analytical solutions on enterprise data platforms, cloud platforms like AWS, containerisation tools like Kubernetes, or CI/CD pipelines for scalable deployment.
Self-driven and able to manage data science tasks independently, while being open to guidance from senior team members.
Proactive and adaptable, comfortable juggling multiple tasks and delivering results in a fast-paced environment.
Enjoys solving complex problems and translating business and regulatory challenges into clear analytical solutions.
Thrives working collaboratively across functions, including with product managers, engineers, and business teams.
Can communicate analytical findings clearly and persuasively to both technical and non-technical audiences.

Responsibilities

Work closely with business teams to understand their data needs, contributing to data science projects that deliver predictive models, dashboards, and other analytical products.
Help ensure the integrity and accuracy of data by assessing and validating data quality, identifying anomalies, and working with data engineers to resolve data issues.
Apply a range of analytical approaches—from descriptive analytics to advanced machine learning—to develop models for risk scoring, fraud detection, and regulatory reporting that inform operational and strategic decisions.
Translate analytical findings into clear visualisations and actionable recommendations for both business teams and leadership.
Champion data literacy and good data practices across the organisation, helping to build a culture that values data as a strategic asset.

Benefits

1-year contract with potential for a 1-year extension and consideration for permanent tenure thereafter.
Opportunity to work on high-impact projects that detect fraud and protect citizens.
Contribute to building a data-driven culture that values data as a strategic asset.