Data Scientist / Data Engineer
About the job
About the Data Scientist / Data Engineer role
Key Responsibilities:
- Work with policy and communications officers, product owners, engineers, domain experts and subject-matter specialists to understand user needs and translate them into clear analytical and machine-learning problems
- Develop and maintain robust evaluation frameworks and datasets for natural language, generative AI and other machine-learning use cases
- Design and conduct experiments to assess and improve model quality, accuracy, consistency, reliability, latency and cost
- Explore and evaluate appropriate models, techniques and emerging technologies, recommending solutions based on evidence, user needs and operational considerations
- Perform systematic error analysis, identify performance gaps across use cases and user segments, and priorities improvements with the team
- Establish suitable automated and human-evaluation approaches, recognizing the limitations and risks of individual metrics and AI-assisted evaluation
- Partner with engineers to integrate validated improvements, define quality checks and monitor performance in production
- Ensure that data, experiments and model decisions are reproducible, well documented and aligned with responsible AI, privacy and security requirements
- Communicate findings, trade-offs and recommendations clearly to technical and non-technical stakeholders across the organization
Requirements:
- A degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Computational Linguistics or a related quantitative discipline, or equivalent practical experience
- Demonstrated experience using data science or machine learning to solve real-world problems, preferably involving natural language processing, generative AI, search or information retrieval
- Strong programming skills in Python and working knowledge of SQL, data processing, version control and software-development practices
- Sound understanding of statistics, experimental design, evaluation methodology, sampling, error analysis and model validation
- Experience working with unstructured text or other complex data types, and evaluating machine-learning or generative AI systems beyond a single aggregate metric
- Familiarity with modern NLP and AI concepts such as embeddings, language models, prompt design and model evaluation
- Ability to write maintainable code and work with engineers to bring data-science solutions into production
- Strong analytical, problem-solving and communication skills, with the ability to explain technical findings and trade-offs clearly to diverse audiences
- A proactive and collaborative mindset, willingness to learn, and motivation to improve public services and communications through technology
Preferred Qualifications:
- Experience with multilingual NLP, translation quality evaluation, or working with linguists and language reviewers
- Knowledge of Chinese, Malay or Tamil, or familiarity with Singapore’s multilingual communications landscape
- Experience with cloud-based AI services, vector search, MLOps, production monitoring or responsible AI practices
- Experience developing AI-enabled products in government, communications, regulated or other high-assurance environments
- An understanding of Singapore’s public communications landscape and the needs of public-sector stakeholders

