# Senior / Data Scientist, AI Programme (MOE)

**Company**: Government Technology Agency (GovTech)
**Location**: Singapore
**Experience**: senior
**Job type**: contract
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/govtech/jobs/4007799201?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_65f101dc-b69

## Description

The Government Technology Agency (GovTech) is the lead agency driving Singapore's Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government's capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.

At GovTech, we offer a purposeful career to make lives better. We empower our people to master their craft through continuous and robust learning and development opportunities all year round. Our GovTechies embody our Agile, Bold and Collaborative values to deliver impactful solutions.

The AI Programme at Singapore's Ministry of Education (MOE) develops AI products and shared capabilities to support teaching, learning and the work of schools. Our teams bring together product management, engineering, design and data science to identify useful applications, test them with users and improve them through evidence.

We are looking for a hands-on Senior Data Scientist to build, evaluate and improve these applications. You will work closely with product teams and education-domain colleagues to translate user needs into practical AI solutions, improve their behaviour and establish whether they deliver meaningful benefits in real settings.

Responsibilities:

- Work with product managers, engineers, designers and domain experts to understand user needs, identify suitable AI approaches, and define measurable outcomes and quality expectations

- Build and iterate on AI prototypes and workflows, using machine learning, large language models, retrieval and tool use where appropriate

- Improve AI behaviour through prompt development, structured experimentation and error analysis

- Design evaluations that reflect how products are used

- Combine human evaluation with automated methods, checking that automated scores align with human judgement and reveal meaningful differences between approaches

- Work with engineers to build reusable evaluation tools, versioned datasets and regression checks

- Use product data, user feedback and targeted experiments to assess usefulness and outcomes

- Translate findings into clear recommendations on product priorities, release readiness and further improvements

- Apply appropriate data-protection and responsible-AI practices

- Mentor colleagues, review evaluation approaches and analyses, and share practical methods that other teams can reuse

Requirements:

- Substantial experience in applied data science or machine learning

- Hands-on experience building and evaluating AI applications, including LLM-based systems

- Strong Python programming skills and working proficiency in SQL

- Sound foundations in statistics and experimental design

- Experience translating product goals and subjective quality expectations into measurable criteria

- Ability to work through ambiguous problems and collaborate effectively with product, engineering and domain colleagues

Preferred Skills:

- Experience in one or more of the following would be an advantage:

- Retrieval-augmented generation, AI agents, tool-use workflows or multimodal AI applications

- Automated evaluation pipelines, production monitoring, AI safety or robustness testing

- Education products, human-AI interaction or evaluating systems where quality depends on context and professional judgement

- Product experimentation and measuring improvements in user outcomes or productivity

- Taking AI prototypes into practical use in cloud environments

## Skills

### Required
- Python
- SQL
- machine learning
- data science
- statistics
- experimental design

### Nice to have
- retrieval-augmented generation
- AI agents
- tool-use workflows
- multimodal AI applications
- automated evaluation pipelines
- production monitoring
- AI safety
- robustness testing
- education products
- human-AI interaction

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/govtech/jobs/4007799201?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)