Tech – Data Scientist: Tech for Public Good - AI Innovation Team

Important

Interested in this project? When applying, remember to indicate the Project Title as listed above in the application form.

Role

Data Scientist

Division

AI Practice

Level

Undergraduate

Internship Duration

6 months, 12 months

Project Description

Interested in this project?

Submit your application and indicate this project as your preference.

Apply Now!

Back to Data Scientist listings

The AI Innovation team is part of GovTech's AI Practice. We stay at the forefront of artificial intelligence research and help product teams adopt cutting-edge technologies to improve operational outcomes across government and deliver tech for public good. As a Data Scientist in the AI Innovation team, you will drive AI transformation in high-impact problem spaces by identifying and researching relevant AI techniques, conduct experiments, and deliver sound solutions through proof-of-concepts.

Learning Outcomes

- Project/product scoping: Identify and prioritise opportunities for high-impact and technically challenging application of AI to transform strategic domains and functions across the Government - AI engineering: Identify and research relevant AI techniques, conduct experiments, and deliver sound solutions through proof-of-concepts - Evaluation techniques: Develop and implement rigourous evaluation techniques to assess and test performance, frequently in innovative areas - Stakeholder management and deployment: Collaborate with relevant stakeholders and engineering teams to ensure seamless transition of successful prototypes into production-ready solutions

Prerequisites

- AI Expertise: Deep understanding of traditional ML algorithms (e.g. logistic regression, random forests), and transformers and related architecture - Deep knowledge of theory and applications of Generative AI: Prompt engineering, RAG, LLM fine-tuning, agentic AI, etc. - Strong programming skills in Python and willingness to work with additional programming languages as required - Preferred: Comfort with deployment of models and prototypes, working with platforms such as AWS, GCP, and familiarity with DevOps concepts such as CI/CD.