2027 Winter - GRM, FC Insights and Analytics Intern (4 Months) at RBC in Toronto, ON

Job description

Job Description What is the opportunity? Are you interested in the opportunity to work as a Financial Crime Analytics Student at RBC? By applying for this job posting, you will be considered for multiple roles available across RBC Global Financial Crime & Compliance. Some exciting roles you'll be considering are: Winter – GRM, FC Insights and Analytics Intern What will you do? Support the design, development, and optimization of AML/Sanctions/ATF client and payment screening models Assist in analyzing screening model performance data and identifying areas for tuning and improvement Contribute to the development of Model White Papers and documentation to communicate screening solutions to stakeholders Support data quality assessments and escalation tracking related to screening model effectiveness Analyze complex datasets to identify patterns, anomalies, and insights relevant to financial crime detection Utilize analytics tools and databases to extract, transform, and load screening-related data Collaborate with cross-functional compliance and technology teams to support screening program enhancements Research industry best practices and emerging technologies in financial crime prevention Be an active contributor to your team while building knowledge of AML/Sanctions regulatory requirements Work in an agile team environment supporting end-to-end delivery of compliance and risk initiatives What do you need to succeed? Must-have Currently enrolled at a Canadian post-secondary institution with a focus on data science, computer science, mathematics, statistics, or related quantitative discipline Strong analytical and critical thinking skills with attention to detail Excellent interpersonal and communication skills (verbal and written) Self-driven, reliable, and capable of working in a fast-paced, regulated environment Programming skills in one or more languages (e.g., Python, R, SQL) Proficiency with MS Office (Excel, Word, PowerPoint) including advanced Excel functions Ability to extract, transform, and analyze large volumes of data Understanding of data visualization concepts and tools Nice-to-have Familiarity with data visualization tools (Tableau, Splunk) Experience with statistical modeling or machine learning concepts Knowledge of financial services, compliance, or risk management Experience with relational databases or data warehouse concepts Familiarity with AML/Sanctions screening applications or financial crime concepts Experience working with open-source frameworks (Hadoop) What's in it for you? Network and build lasting relationships with students and professionals across RBC's Global Financial Crime organization Gain hands-on experience in a highly regulated, mission-critical business area Leaders who support your development through coaching, mentorship, and learning opportunities Work in a dynamic, collaborative, and highly performing team dedicated to financial crime prevention Ability to make a real difference in protecting RBC and the financial system Participate in fun events and professional development activities Comfortable work environment with flexible dress code Please note: This posting is for a 4-months Winter 2027 Student placement with a start date of January 2027, and end date of April 2027. In order to be eligible for this 4-months Student position, you must either: Be returning back to school after the work term end-date of April 2027 ; or If you are not returning back to school (i.e. are graduating in April 2027), you must require the full 4-months work term as a mandatory component to in order to graduate successfully. Please ensure that you meet these eligibility requirements before applying - candidates who apply but are found to be ineligible are not able to be considered. We encourage you to apply as soon as possible as we accept applications on a rolling basis, but please note that the formal application deadline is September 20, 2026. Should you be selected to progress, someone from our team