Generative AI & Portfolio Analytics Internship

ocbc

Singapore

On-site

SGD 11,000 - 22,000

Part time

2 days ago
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Job summary

OCBC invites motivated students to join the Portfolio Insights & Validation team as Gen AI interns. You will help develop AI-powered portfolio reporting and risk management solutions, and contribute to automation of portfolio commentary and insights.

The role offers hands-on experience with data analysis, model validation concepts, and emerging AI applications within a banking context. Ideal candidates are curious, technically proficient in Python, and eager to learn how AI can transform risk

Qualifications

  • Currently pursuing an undergraduate or postgraduate degree.
  • Proficient in Python and comfortable developing scripts for data analysis and automation.
  • Strong interest in Generative AI, data analytics, and technology innovation.

Responsibilities

  • Develop, test and evaluate Gen AI initiatives to enhance portfolio reporting and risk management.
  • Assist in coding and designing Gen AI capabilities to automate portfolio commentary and reporting insights.
  • Analyze data and business requirements to identify AI-driven improvement opportunities.
  • Collaborate with validation and reporting teams to review reports and ensure outputs are meaningful.
  • Identify opportunities to streamline processes and boost productivity with AI tools.
  • Conduct research on emerging AI technologies and potential use cases in risk management.
  • Work with risk, analytics and business teams to gather requirements and test solutions.
  • Support ad-hoc analytics, innovation and portfolio management projects.

Skills

Python
Data analytics
Generative AI

Education

Undergraduate or postgraduate degree student

Job description

OCBC invites motivated students to join the Portfolio Insights & Validation team as Gen AI interns. You will help develop AI-powered portfolio reporting and risk management solutions, and contribute to automation of portfolio commentary and insights.

The role offers hands-on experience with data analysis, model validation concepts, and emerging AI applications within a banking context. Ideal candidates are curious, technically proficient in Python, and eager to learn how AI can transform risk

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