Crédit Agricole Corporate and Investment Bank (ISAP Singapore) Careers

Who we are

Crédit Agricole Corporate and Investment Banking (Crédit Agricole CIB) is the corporate and investment banking arm of Crédit Agricole Group, world’s 12th largest bank by total assets.

• Our Singapore center (“ISAP” or “Information Systems Asia Pacific”) is the 2nd largest IT setup (after Paris Head Office)” for Crédit Agricole CIB's worldwide business. We work daily with international branches located in 30 markets by:

-          Envisioning and preparing the Bank’s futures information systems

-          Partnering and supporting core banking flagships and transverse areas in their large scale development projects.

-          Providing premium In-house Banking applications,

• This unique positioning empowers us to bring our core banking business a sustainable competitive advantage on the market.
• We seek innovative and agile people sharing our mindset to support ambitious and forthcoming technological challenges.

The Department

Capital Markets IT (CMI) involves technology solutions and systems used in financial markets for trading, investment, and related activities. This includes electronic trading platforms, risk management systems, market risk, counterparty risk, algorithmic trading, data analytics, and regulatory measures. The use of advanced technologies like API’s, artificial intelligence and cloud solutions are also becoming increasingly prevalent in capital markets to enhance efficiency and decision-making processes.

Role Overview

We are looking for an AI/ML intern to join our Data and Regulatory Reporting team. This is a critical role for our Capital Markets IT department, responsible for designing, building, and deploying cutting-edge AI/ML solutions to improve data quality, streamline regulatory reporting processes, and drive innovation across our systems.

As an AI/ML intern, you will play both an individual contributor and leadership role, contributing to technical direction, and collaborating cross-functionally with business analysts, DevOps, and infrastructure teams. You will work with the latest tools and technologies in machine learning, including AWS SageMaker, AWS Bedrock, and large-scale time series modeling.

Mission

As an intern, your mission is to become a valuable asset to our organization by:

AI/ML Systems Design and Development

• Enhance and maintain intelligent anomaly detection pipelines by integrating traditional rule based systems with modern time series forecasting and ML models.
• Build scalable, production-grade machine learning pipelines using Python, TensorFlow, PyTorch, and Scikit-learn.
• Design and deploy real-time and batch inference services using AWS SageMaker, Lambda, and Bedrock.
• Implement generative AI and LLM-based solutions to enhance system diagnostics, log interpretation, anomaly explanation and to dynamically generate rules.
• Develop and maintain backend services using Java Spring Boot and frontend applications using React.
• Utilize MongoDB for efficient data storage and retrieval in anomaly detection systems.

Automation and Infrastructure

• Lead the development of fully automated ML workflows, from data ingestion to model retraining and monitoring, using shell scripts, AWS Step Functions, and CI/CD pipelines.
• Deploy, monitor, and manage models on cloud and on-premises hybrid environments, ensuring scalability and low-latency performance.
• Apply MLOps principles to streamline experimentation, deployment, and version control of ML models.

Data Visualization and Communication

• Develop intuitive web-based dashboards to visualize anomalies and model outputs, supporting business analysis and stakeholder insights.
• Collaborate with regulatory reporting teams to tailor model outputs to compliance needs across MAS, HKMA, EMIR, and other frameworks.

Qualifications and Profile

• Pursuing Master’s degree or Bachelor’s degree in computer science, Software Engineering, or related field.
• Familiarity with frameworks such as Scikit-Learn, Keras, Tensor Flows etc.
• Understanding of tracking data quality using ML methods.
• Knowledge of prompt engineering techniques and LLM fine-tuning.
• Understanding of responsible AI principles and ethical considerations in generative AI applications.
• Familiarity with tools like OpenAI API, Hugging Face transformers, or similar generative AI platforms.
• Excellent problem-solving, analytical skills, attention to detail, & curious.
• Independent contributor with the ability to collaborate and work effectively within the team.
• Excellent written and verbal communication and interpersonal skills.
• Passion for automation, standardization and best practices.
• Willingness to learn and adapt to latest/new technologies.

The scope will be adapted depending on the situation and the progress of the trainee.