[What the role is]

SSG is a dynamic and forward-thinking organization dedicated to empowering individuals and shaping the future of Singapore's workforce. As a statutory board under the Ministry of Education, SSG leads the charge in driving the SkillsFuture movement, a national initiative that promotes lifelong learning and skills development. With a strong focus on innovation and collaboration, SSG works closely with employers, training providers, and individuals to create a vibrant ecosystem of learning and growth. By offering a wide range of initiatives, programs, and funding schemes, SSG enables individuals to unlock their full potential, acquire new competencies, and stay ahead in a rapidly changing job market.

Join the Data Strategy & Analytics Division (DSAD) team to grow SSG into a data-mature organization where we use data pervasively and securely to deliver on our business missions:
• Develop and drive SSG’s data strategy, including LOIs, data competency, and maintaining strong links with CIO Office
• Develop, implement and maintain comprehensive data governance and management framework that complies with WOG requirements Implement Lines of Inquiries
• Support data management and exploitation
• Develop MLOps and instil best practices

[What you will be working on]

The Data Scientist in the Data Strategy and Analytics Division reports to the Principal Manager and plays a pivotal role in deriving business insights from large and real-time datasets for fraud and risk management, strategic planning as well as operational efficiency. This position will develop, deploy and maintain data analytic models as well as have opportunities to also collaborate with other public agencies to introduce and enhance data science capabilities (such as Jobs and Skills) for the organisation. As the domain expert in data analytics the Data Scientist is also expected to coordinate, strategize and guide the SSG officers performing data analytics work to achieve efficiency and accuracy.

• Data Analysis & Model Development

• Research and develop statistical and machine learning models for comprehensive data analysis

• Utilize algorithms and models to mine big data, perform data and error analysis, and ensure data uniformity and accuracy

• Apply data mining techniques and perform statistical analysis to generate insights at scale

• Collaboration & Solution Development

• Work closely with both internal and external stakeholders to understand analytic needs and develop effective solutions

• Create machine learning-based tools or processes, such as recommendation engines, and monitor their performance through A/B testing and predictive capabilities

• Communicate analytic solutions to stakeholders and implement necessary improvements to operational systems

• Innovation & Capability Building

• Identify relevant structured and unstructured data sources for mining meaningful insights

• Build prototype analysis pipelines iteratively to provide scalable insights

• Contribute to building data analytics capabilities across the organization, emphasizing the strategic value of data in achieving business objectives

[What we are looking for]

• Tertiary qualification in a quantitative discipline such as Computer Science, Economics, Statistics, or Applied Mathematics.

• 3-8 years of experience in computer science, applied mathematics, or other quantitative/computational disciplines.

• Proven experience in data visualization tools (e.g., Tableau) and data analysis/processing tools (e.g., R, Python).

• Experience with Cloud Technology (e.g., AWS data and analytics Tech Stack) and distributed computing tools (e.g., Hadoop/Spark).

• Demonstrated ability in building machine learning models at scale, using real-time data pipelines on platforms.

• Strong analytical skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.

• Proficiency in data engineering, including SQL and manipulating structured and unstructured data sources for analysis.

• Advanced skills in pattern recognition and predictive modeling.

• Experience or specialization in fraud prevention/detection, compliance, forensics, or Jobs and Skills related analysis will be considered advantageous.

• Excellent communication and presentation skills, with a strong emphasis on collaboration and innovation.