Lead Data Scientist, AML Analytics

RBC; Vancouver; Presencial; CAD 140.000 - 180.000; Jornada completa

Descripción de la vacante

RBC is seeking a Lead Data Scientist, Global AML Transaction Monitoring, to build and tune AML/ATF transaction monitoring models. You will identify suspicious activity, analyze large datasets, and deliver actionable intelligence to the Global AML program while aligning with risk management practices.

You will develop ML and rule-based monitoring solutions, document model performance, and collaborate with cross-functional teams to prioritize and improve monitoring capabilities.

Formación

• University or Master degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, or related quantitative field).
• 5+ years of experience in in-depth data analytics.
• Expertise in analyzing and manipulating large datasets with Python and Scala/Spark.
• Proficiency with SQL, Hive databases and GitHub.
• Strong capability in exploratory data analysis and feature development.
• Understanding of AML and Financial Crime fundamentals.
• Ability to translate business needs into detection models and communicate model risk analytics insights.

Responsabilidades

• Develop, tune, and maintain AML Transaction Monitoring ML, rule-based solutions.
• Develop new AML 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 leadership.
• Collaborate with stakeholders to prioritize and implement monitoring solutions.
• Work with Analytics teams to address RBC risk exposure and tune monitoring solutions as needed.
• Identify opportunities to apply new technologies to AML analytics.

Conocimientos

Python

Scala Spark

SQL

Hive

GitHub

Data analytics

AML fundamentals

Communication skills

Model risk literature

Educación

University or Master degree in an analytical field

Herramientas

Python

Scala

Descripción del empleo

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

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 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.