Senior Data Analyst (Credit Risk, Bank) at Renmoney

Job Description

We are seeking a highly skilled and experienced Senior Data Analyst to join Renmoney's Credit Risk team. As a Senior Data Analyst, you will play a crucial role in supporting various teams such as Decision Science, Portfolio Management, Collections, Policy, and Risk by monitoring and tracking various parameters to ensure effective credit risk management. You will work closely with cross-functional teams, utilizing your expertise in data analysis, visualization, and programming to provide actionable insights and drive data-driven decision-making. 

Data Analysis and Visualization: 

• Collect, analyze, and interpret complex credit risk data from multiple sources to identify patterns, trends, and potential risks. 
• Design and develop comprehensive dashboards and reports using Power BI to visually represent key performance indicators and provide insightful visualizations to stakeholders. 
• Collaborate with teams to define data requirements and ensure data integrity and accuracy in the credit risk domain. 
• Provide clear and concise summaries of analysis findings to management and stakeholders, highlighting significant risks, opportunities, and recommendations. 

Model Monitoring and Validation: 

• Monitor and validate credit risk models to ensure their accuracy, effectiveness, and adherence to regulatory requirements. 
• Develop and implement proactive strategies to identify model performance deviations and provide recommendations for model enhancements or adjustments. 
• Collaborate with Decision Science teams to understand model methodologies, assumptions, and limitations, and provide feedback on model performance. 

ETL Processes and Data Management: 

• Utilize your expertise in SQL and ETL processes to extract, transform, and load data from various sources into the credit risk data warehouse. 
• Develop and maintain data pipelines, ensuring the smooth flow of data and data integrity throughout the credit risk domain. 
• Collaborate with IT teams to optimize data storage and access, ensuring efficient and secure data management practices. 

Collaboration and Support: 

• Work closely with cross-functional teams including Decision Science, Portfolio Management, Collections, Policy, and Risk to provide analytical support, answer ad-hoc data queries, and address data-related challenges. 
• Collaborate with stakeholders to understand business requirements and translate them into actionable insights and data-driven solutions. 
• Stay up-to-date with industry trends, best practices, and emerging technologies in data analysis, visualization, and credit risk management. 

Requirements: 

• Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, or a related discipline. A Master's degree is preferred. 
• Proven experience (5+ years) working as a Data Analyst in the credit risk domain, preferably within the banking industry. 
• Strong proficiency in Power BI for data visualization and reporting. 
• Proficiency in Python for data analysis and programming. 
• Good knowledge of R for statistical analysis (preferred). 
• Expertise in SQL for data extraction, transformation, and querying. 
• Experience with Postgres or other relational databases. 
• Solid understanding of ETL processes and data management best practices. 
• Strong analytical skills with the ability to identify trends, patterns, and potential risks. 
• Excellent communication skills to present complex findings effectively and insights to stakeholders. 
• Ability to work collaboratively in a cross-functional team environment. 
• Strong attention to detail and commitment to delivering high-quality work.