Manager, Quantitative Analytics & Monitoring

Job Description

What is the opportunity?

The Quantitative Analytics & Monitoring (QAM) team solves strategic problems in support of Credit & Fraud Management. We leverage data to influence strategies, measure the impact of business decisions, and pull together the top-line story of our business impact.

As we scale our analytics function and modernize our infrastructure, we're looking for analytical professionals who can move beyond reactive dashboarding to proactive insight discovery, finding answers to questions leaders didn't yet know to ask. You'll work embedded in business squads across our key pillars (Collections & Recoveries, Commercial, Credit Cards, Personal Financing Products, Deposits, Digital, Payments, Scams and Performance & Portfolio Monitoring), building deep context on fraud and collections operations, and surfacing patterns and opportunities that drive strategic decision-making.

You will work with people who are passionate about analytics, thrive in a diverse and inclusive culture, and are committed to building CFM as the industry gold standard for fraud and collections management.

What will you do?

• Collaborate with Credit and Fraud Management partners to understand core business goals and strategic priorities; embed yourself in their operations to build context and identify unanswered business questions

• Deliver proactive business insights that anticipate stakeholder needs—moving beyond reactive reporting to recommend strategic and operational decisions grounded in data

• Develop, test, and refine hypotheses on data trends, customer behavior, and fraud/collections patterns; challenge assumptions and validate insights through rigorous analysis

• Build and own analytical products (dashboards, analyses, decision frameworks) that enable leaders to operate from a single authoritative view and act with confidence

• Contribute to broader analytics transformation including cloud migration, real-time monitoring, and AI/ML scaling initiatives

• Collaborate on innovation and emerging technology pilots (GenAI, advanced ML, emerging fraud vectors) to stay current and drive competitive advantage

What do you need to succeed?

Must Have:

• Business acumen, curiosity, strong communication, and solid technical skills

• 2+ years of analytics-related experience in Business Analytics, Consulting, Technology, or related fields

• 2+ years' experience with data tools including SQL, Python or R, and visualization platforms (Tableau, Looker, Power BI, etc.)

• Experience working with complex, large-scale relational databases and comfort adopting emerging technologies

• Proven ability to translate data into strategic narrative; collaborate with stakeholders to align business and data requirements

• Proactive mindset: Ability to identify unanswered questions and take initiative to research and recommend solutions

Nice to Have:

• University degree in a quantitative field (statistics, math, computer science, economics, etc.)

• Experience with Retail, Commercial, or Consumer Banking products

• Exposure to fraud or collections analytics

• Experience with cloud platforms (AWS, GCP, Azure) or modern data infrastructure

• Familiarity with Python/R for statistical modeling or machine learning applications

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits

• The opportunity to learn about the business models across both Personal and Commercial Banking and take on progressively greater accountabilities

• Leaders who support your development through coaching and managing opportunities

• Ability to make a difference and lasting impact

• Work in an agile, collaborative, progressive, and high-performing team

Job Skills

Artificial Intelligence (AI), Business Analytics, Business Insights, Data Mining, Data Science, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Programming Languages, Python (Programming Language), Statistical Analysis, Structured Query Language (SQL), Tableau (Software)

Additional Job Details

Address:

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

PERSONAL & COMMERCIAL BANKING

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-04-24

Application Deadline:

2026-05-15

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.