To be a part of a global, exciting and forward-thinking Data Products team within Internal Audit that are focused on building insight-driven applications to provide enhanced assurance across Sarbanes-Oxley (SOX) & Internal Audit Shared Services. As RBC continues to evolve in response to new challenges that impact financial markets across the globe, Internal Audit have been proactive in transforming their approach from traditional auditing, to data-informed decision making when assessing and challenging the management of risk across the business.

The RBC CAE Group leverages a unique perspective— with a coordinated view across the entire business—to deliver valuable advice that not only gives assurance, but that illuminates a bigger picture, connects dots, builds best practices and broadens possibilities. We connect intelligence to protect and enable RBC.

• Apply your skills in data exploration, statistical analysis and machine learning on a diverse range of data sources to identify insights and opportunities to develop data products.
• Use your curiosity and own initiative to develop innovative solutions to a wide and ever-changing set of complex problems across RBC.
• Automate and productionize the testing of key business and IT controls to enable auditors in continuously monitoring key risks across the enterprise.
• Collaborate with other data analysts, data engineers, data product leads and data scientists within Internal Audit to scale your ideas from concept to production.
• Help develop the vision for automated control test and process enhancements, supporting with the development of business cases, development requirements, product roadmaps, and product backlogs.
• Take ownership in driving the Data Products strategy across a wide portfolio of internal audit.
• Design, develop and maintain productionized applications and dashboards for our end users.

Must have

• Degree in a quantitative field, and experience with either Python or R as well as SQL
• Experience building natural language processing (NLP) and unsupervised learning models
• Strong grasp of fundamentals in statistics (hypothesis testing, regression, inference)
• Ability to own and manage a backlog, with a value-based understanding of all stakeholders. Excellent collaborator and stakeholder management experience.
• Demonstrated experience exploring large, complex datasets for the purpose of anomaly detection and latent pattern recognition

Nice to have

• Experience developing interactive and sophisticated dashboards in Tableau (or similar tool) and experience working with Dataiku
• Understanding of software engineering design principles
• Demonstrated experience building strong relationships and communicating effectively with both technical and non-technical stakeholders
• Project Management Experience and Lean Six Sigma Yellow Belt or equivalent in process improvement