Intern - Commercial Banking SG

Key Responsibilities:

• Data Management: Assist in the collection, organization, and maintenance of data related to risk management activities, including but not limited to credit risk, operational risk, market risk, and compliance data.
• Data Processing: Utilize Python programming skills to perform data cleaning, transformation, and analysis tasks. Apply appropriate algorithms and techniques to handle large datasets effectively.
• Business Analytics: Collaborate with the Commercial Banking Management team to analyze and interpret data to identify trends, patterns, and potential business opportunities. Assist in developing models and reporting frameworks.
• Product Management : Shadow a product manager with an assigned financial product as part of your portfolio and you will learn the entire product management end-to-end lifecycle of your product suite. Based on this, you will conduct analytics and propose refinement and changes to improve efficiency of the product performance.
• Reporting and Documentation: Prepare clear and concise reports, summaries, and visualizations of data analysis findings for stakeholders, including senior management and regulators. Ensure accurate and timely reporting of business-related information.
• Stakeholder Collaboration: Communicate effectively with stakeholders, including risk managers, business unit leaders, and IT professionals, to understand their data needs and requirements. Provide insights and recommendations based on data analysis results.
• Process Improvement: Identify opportunities to streamline data management and analytics processes, enhance data quality, and optimize business and risk management practices. Propose and implement solutions to improve efficiency and effectiveness.
• Research and Learning: Stay updated with industry trends, best practices, and emerging technologies in data management, data processing, and risk analytics. Continuously enhance knowledge and skills in Python programming and data science techniques.

Requirements:

• Currently pursuing a degree in a relevant field such as Data Science, Computer Engineering, Computer Science, Statistics, or a related discipline.
• Strong knowledge and hands-on experience in Python programming for data processing and analysis. Required to understand the different Python modules.
• Familiarity with data processing techniques, such as data cleaning, transformation, and integration.
• Excellent analytical skills with the ability to interpret and draw insights from complex data sets.
• Strong communication and presentation skills to effectively convey technical concepts to non-technical stakeholders.
• Detail-oriented mindset with a strong commitment to accuracy and data integrity.
• Ability to work independently and collaborate effectively in a team-oriented environment.
• Demonstrated problem-solving abilities and a proactive attitude towards process improvement.
• Knowledgeable in Data usage and MIS concepts.
• Self-motivated and results-oriented