2023 Spring Internship – Data Analytics

at GXS Bank
Published October 28, 2022
Location Singapore, Singapore
Category Data Science  
Job Type Internship  


About GXS

We are living in dynamic times. Technology is reshaping how we live, and we want to use it to redefine how financial services are offered. Digibank is a Grab-Singtel consortium, aimed at enabling the underserved groups to easily access transparent financial services that are embedded in their everyday activities, helping them achieve a better quality of life. We are incredibly excited to build a Digital Bank with the right foundation using data, technology and trust to solve problems and serve customers

Get to know our Team:

The DSA team aims to deliver impact and insights to the Digibank businesses by using AI and analytics to harness both internal and external data. We place strong emphasis on learning and strive to adopt state of the art technology that could optimally utilize the data for the benefits of our businesses.

As an intern as part of Campus Recruiting, you will be part of the team who delivers AI and analytics solutions across different businesses within the bank and conduct bluesky research that could yield great benefits to the firm.

Duties And Responsibilities

  • DS track: Data Science Projects - Contributing to the DSA code base by adding new codes, refactoring existing codes, reviewing codes.
  • DA track: Analytics Projects - Do ETL, feature/metrics engineering and build dashboards to show insights and results.
  • All tracks:
    • Research - Participate in our team to conduct bluesky research that is risky but yet potentially may yield high returns. Examples of bluesky research include using neural databases for information querying, handling confounding variables in causal models with deep learning, self-supervised contrastive learning.
    • Modeling - Optional. May be required to help in building machine learning models for certain projects.
    • MLOps - Optional. May be required to improve or fix components in our current MLOps architecture.

Learning Objectives

  • Learn how to conduct research and be exposed to the state of the art machine learning techniques.
  • To gain experience in software engineering and MLOPs, and tasks performed by data scientists such as ETL, feature engineering, modeling, analytics dashboard building.
  • Learn the best practices of working effectively in a technical team, with product managers, data scientists and engineers.

The Must-Haves

  • Only for candidates who are available from Jan 2022 - June 2022 or Dec 2020 - May 2021; Part time internships are welcome
  • Must be strong in Python and SQL
  • Knowledge in building dashboards using Tableau (can be self-training through online courses)
  • Knowledgeable about Machine Learning and Statistics