Data Scientist (RAD)

[What the role is] SWDA is a dynamic and forward-thinking organization dedicated to empowering individuals and shaping the future of Singapore's workforce. As the National Skills Authority, SWDA 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, SWDA 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, SWDA enables individuals to unlock their full potential, acquire new competencies, and stay ahead in a rapidly changing job market. The National Jobs-Skills Data Office, under the Research & Analytics Division, serves three core functions: • Data and Algorithms Innovation and R&D: Undertake development of new data models and algorithms to serve whole of government’s jobs-skills intelligence needs; • Jobs-Skills Product Management, Development and Delivery: Manage and enhance jobs-skills products, which includes UX/UI design and end-to-end product life cycle management; • Data Management and Operations: Centrally manage data quality, data models and data infrastructure to support internal and external users Come join this game-changing team in SWDA, where we empower employers, citizens, training providers, and policymakers to make informed decisions by using a user-centered approach, providing trusted source of jobs-skills data and insights, and a common set of jobs-skills taxonomies for a skills-first future! [What you will be working on] As a Data Scientist, you will be a key member of the Data and Algorithms Innovation and R&D team, transforming complex data into meaningful insights that drive strategic decisions, building statistical, machine learning and graph models to solve real-world problems, designing experiments to measure impact and communicating findings clearly to both technical and non-technical stakeholders. By combining analytical thinking, programming skills and policy understanding, you will help uncover opportunities, solve real-world problems and guide data-informed decision-making across SWDA. • Develop and deploy advanced analytical models to extract deeper insights from jobs, skills, and tasks data, applying statistical and machine learning techniques including feature engineering, model selection, and validation using appropriate performance metrics • Design and build scalable data infrastructure by creating modular, reusable data pipelines and prototyping advanced analytics solutions that operationalize insights to support evolving stakeholder needs across various partnership levels • Translate complex data signals into strategic insights through close collaboration with product and policy teams, ensuring analytical outputs meaningfully inform workforce and industry planning decisions that align with national skills development objectives • Drive continuous analytical improvement by evaluating and enhancing existing methodologies, incorporating new data sources, external datasets, and robust model validation frameworks to strengthen the analytical foundation • Lead analytical partnerships and collaborations by scoping and supporting projects with internal divisions and external partners, translating stakeholder requirements into well-defined data science problem statements and delivering comprehensive analytical solutions • Contribute to national jobs-skills data assets including the development of structured taxonomies, entity extraction pipelines, and knowledge graph representations that support Singapore's skills intelligence ecosystem • Champion research-backed innovation by staying current with emerging analytical techniques, tools, and methodologies, ensuring SIPD maintains cutting-edge capabilities in workforce analytics and skills intelligence [What we are looking for] Experience: • Background in data science, statistics, machine learning, or related quantitative disciplines with demonstrated experience applying analytical techniques to both structured and unstructured datasets • Proficiency in Python and SQL for data analysis, modeling, and data pipeline development, with experience in machine learning model deployment or productionization • Experience with unstructured data processing, particularly text or language data using natural language processing, language models, or text analytics techniques • Proven track record in developing, evaluating, and validating statistical or machine learning models using appropriate validation approaches and performance metrics • Familiarity with data visualization tools and techniques for presenting complex analytical insights to diverse audiences • Knowledge of labour market, workforce, or skills-related data and analytics Analytical and Problem-Solving Competencies: • Strong analytical mindset with ability to break down complex or ambiguous problems into structured analyses and testable hypotheses • Experience in translating business requirements into technical solutions and communicating findings effectively to diverse stakeholder groups Collaboration and Communication Skills: • Excellent communication abilities to explain analytical findings and technical concepts clearly to non-technical stakeholders, including policy makers and senior leadership • Self-driven contributor with strong ownership of analytical workstreams and proven ability to collaborate effectively across product, research, and policy teams • Experience in managing multiple projects simultaneously while maintaining high standards of analytical rigor and delivery quality Successful candidates will be offered a contract in the first instance and may be considered for an extension or be placed on a permanent tenure. Candidates are encouraged to sign up for a Careers & Skills Passport (CSP) account and include your CSP public profile in your resume. Please ch…