Intern - Commercial Banking Sg

3 days ago

Singapore CIMB Group Full time

**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.
- 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

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