Associate Director – Credit Risk Analytics
| Company | Royal Bank of Canada |
|---|---|
| Location | Toronto, ON, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Senior |
Requirements
- Degree in Computer Science, Mathematics/Statistics, Engineering, related field or equivalent related experience
- Experience in statistical methods, strong data profiling, cleaning, and mining
- Ability to perform complex data analysis on large volumes of data and present findings to senior leaders in order to inform strategic decisions
- Demonstrated ETL and big data modeling capabilities, with programming experience in large databases/datasets and using Python, Trino
- Deep data knowledge on RBC’s EDW
- Experience on data extract/ingestion against EDL
- Advanced proficiency in developing reports using Tableau
- Exceptional analytical and critical thinking skills with the ability to develop data-driven insights and perform root cause analysis
- Strong communication, collaboration, and problem-solving skills, including data modeling and translating technical expertise into business language
- Proficient in programming languages such as Python, R, SAS, and SQL for data manipulation and analysis
- Experience with data visualization tools (e.g., Tableau, Power BI) and analytics platforms
- Agile mindset with a commitment to continuous improvement and the ability to iteratively enhance modeling or data pipeline processes
- Solid understanding of RBC’s Risk and Finance processes, risk systems infrastructure, and data architecture
- Extensive experience in Data Science and Business Analytics, with a proven track record of enhancing data capabilities and driving business decisions
- Knowledge of data governance frameworks, data quality management, and data security practices
Responsibilities
- Develop in-depth understanding of credit risk across industries or credit products within BFS
- Provide analytical support on Ad Hoc requests originating from stakeholders in business and GRM teams, and senior management
- Develop and implement data products (Dashboards/Reports) to support credit risk management for Commercial & Wholesale portfolios
- Translate business needs into data products by engineering ETL solutions, ensuring data quality and integrity
- Build and iteratively improve data pipelines by navigating enterprise data warehouse and leveraging open-source querying and programming tools
- Engage cross functional stakeholders to enhance data structure and quality for valuable credit risk capabilities and strategies
- Identify and integrate new and innovative data sets to improve existing risk metrics & models and explore new data utilization opportunities for current and future products
Preferred Qualifications
- Demonstrated leadership in cross-functional environment
- Familiar with enterprise risk management framework
- At least 5 years of professional work experience in the area of Data Analytics / Data Science / Business Analytics
- Strong experience in the big data ecosystem, with Hadoop (Hive, HDFS), Apache Spark, and NoSQL/SQL databases
- Strong programming skills, with experience in languages such as Python and SQL
- Strong experience in open source frameworks
- Experience with Natural Language Processing and supervised/unsupervised learning methodologies