Lead Data Scientist, AML Analytics

rbc; Toronto; On-site; CAD 140,000 - 210,000; Full time

Job summary

RBC is seeking a Lead Data Scientist for Global AML Transaction Monitoring in Toronto. You will develop and tune AML/ATF monitoring models, analyze large datasets, and collaborate with stakeholders to enhance risk detection and intelligence across the organization.

The role requires 5+ years of analytics experience, strong Python/Scala skills, AML knowledge, and a track record of delivering robust ML and rule-based solutions in a regulated environment.

Qualifications

• 5+ years of experience conducting in-depth data analytics.
• Bachelor's or Master's degree in analytical field (e.g. CS, Engineering, Math, Statistics).
• Expertise in analyzing and manipulating large datasets with Python and Scala/Spark.
• Proficiency with SQL, Hive databases and GitHub.
• Strong exploratory data analysis and feature development.
• Understanding of AML and Financial Crime Fundamentals.
• Ability to translate technical context into business understanding of models.
• Exceptional attention to detail in documentation and analysis.
• Strong written and verbal communication to explain model risk to stakeholders.
• Translates project needs into effective detection models.

Responsibilities

• Develop, tune, and maintain AML Transaction Monitoring ML and rule-based solutions.
• Develop new AML Transaction Monitoring solutions using data science techniques.
• Create validation-ready model documentation and monitoring methodology per Enterprise Model Risk Management Standards.
• Document model performance metrics and provide recommendations to Director, Transaction Monitoring.
• Collaborate with the Director to prioritise monitoring solution development.
• Collaborate with Monitoring & Analytics teams to remediate RBC risk and implement solutions.
• Collaborate with business partners to improve effectiveness of the monitoring program.
• Identify opportunities to apply new technologies to AML analytics.
• Identify industry best practices for AML Monitoring Committee.

Skills

Data Mining

Data Science

Machine Learning

NLP

Predictive Analytics

Python

Decision Making

Actuarial Modeling

Big Data Management

Commercial Acumen

Spark

Education

Master's degree

Bachelor's degree

Tools

SQL

Hive

GitHub

Scala

Spark

Job description

Job Description

As a Lead Data Scientist, Global AML Transaction Monitoring, you will develop and maintain efficient and effective AML/ATF Transaction Monitoring models that considers regulatory expectations, industry trends and innovation opportunities. You will be required to develop and tune new and existing solutions used to identify suspicious activity, analyze data to identify RBC clients who present an elevated level of risk (financial & reputational) and continuously look for opportunities to provide more relevant and valuable intelligence to the Global AML program.

WHAT WILL YOU DO?

• Develop, tune, and maintain existing AML Transaction Monitoring machine learning, rule-based solutions
• Develop new AML Transaction Monitoring solution using data science techniques
• Develop validation-ready model documentation and monitoring methodology for models, in adherence to Enterprise Model Risk Management Standards
• Create and document model performance metrics, and provide recommendations to the Director, Transaction Monitoring on any findings of model performance
• Collaborate with the Director, Transaction Monitoring to prioritize development of monitoring solutions
• Collaborate with other Monitoring & Analytics teams to identify and remediate RBC risk exposure, and implement / tune transaction monitoring solutions as necessary to address risk
• Collaborate with business partners and internal stakeholders to improve effectiveness and efficiency of transaction monitoring program
• Identify opportunities in applying new technologies to AML analytics
• Identifying industry best practices and new technologies for strategic consideration by the AML Monitoring and AML Governance Committee

WHAT DO YOU NEED TO SUCCEED?

Must have :

• 5+ years of experience conducting in-depth data analytics
• University or Master degree in an analytical field of study (e.g. Computer Science, Engineering, Mathematics, Statistics, or related quantitative field).-
• Expertise in analyzing and manipulating large datasets with Python and Scala/Spark-
• Proficiency and familiarity with different SQL, Hive databases and GitHub-
• Strong capability in exploratory data analysis and feature development-
• Understanding of AML and Financial Crime Fundamentals-
• Strong solution-oriented mindset, capable of synthesizing technical, operational and business context into clear understanding of how models operate-
• Exceptional attention to detail across documentation, testing artifacts, and quantitative analysis-
• Strong written and verbal communication skills; capable of explaining model risk analytics findings to both technical and non-technical stakeholders, as well as tell stories with data meaningfully-
• Understands project's needs and ability to translate these into detection models

Nice to have

• Specific experience in Financial Crime or Transaction Monitoring Analytics roles
• Experience working in specific business or financial industry data domains (i.e. Capital Markets, Wealth Management)
• Experience with supervised and unsupervised learning, and NLP preferred

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, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• A world-class training program in financial services
• Opportunities to do challenging work. Opportunities to take on progressively greater accountabilities. Opportunities to building close relationships with clients
• Access to a variety of job opportunities across business and geographies.

Job Skills

• Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Additional Job Details

Address: 20 KING ST W:TORONTO City: Toronto Country: Canada Work hours/week: 37.5 Employment Type: Full time Platform: GROUP RISK MANAGEMENT Job Type: Regular Pay Type: Salaried Posted Date: 2026-10-19 Application Deadline: 2026-11-14 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 wor