Data Science

Business Function 

As the leading bank in Asia, Transformation & Data (T&D) supports our management on the implementation of the Group’s agenda. Data Chapter, organized under T&D, is committed to create synergies between the data analytics functions across the bank, establish centres of excellence, shared services, and reusable data assets, as well as enhance career opportunities and the sense of community for data professionals. 

Responsibilities 

• Work with senior data scientists to design, build and test machine learning, GenAI, and agentic AI solutions for business use cases. 

• Assist with data preparation, exploratory data analysis, model development, and evaluation. 

• Help maintain project documentation, experiment notes, code repositories, and reusable assets to support good team practices. 

• Share the latest techniques and technologies in AI and data science, participate in a spirit of continuous learning with the team. 

Requirements 

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative field. 

• Knowledge of machine learning and statistics; basic knowledge of software development concepts. 

• Hands-on experience with Python and common data science libraries such as Pandas, NumPy, scikit-learn, Matplotlib, or Plotly. 

• Familiarity with SQL and working with structured datasets. 

• Interest in GenAI, LLMs, prompt engineering, RAG, agentic AI, and related technologies. 

• Good analytical thinking, problem-solving skills, curiosity, and willingness to learn. 

• Good documentation habits and the ability to communicate findings clearly in written and verbal form. 

• Basic familiarity with Git, Jira, Confluence. 

• Ability to work independently, collaborate in a team environment, and take guidance from experienced data scientists and project stakeholders. 

Good to have 

• Exposure to tools or frameworks such as LangChain, LangGraph, Dify, Google Vertex AI, or similar platforms. 

• Exposure to the GCP ecosystem of tools, such as BigQuery for querying datasets or Vertex AI for ML and GenAI experimentation. 

• Experience from academic projects, internships, hackathons, Kaggle competitions, or personal data science projects. 

• Basic understanding of responsible AI, model evaluation, data privacy, or model risk governance concepts. 

• Interest in financial services, banking, or regulated industries. 

Apply Now 

We offer a valuable internship opportunity to gain hands-on experience in a dynamic data science and AI environment. 

We regret that only shortlisted candidates will be notified.