Lead Data Scientist, AML Analytics
RBC is hiring a Lead Data Scientist, AML Analytics in Toronto, Canada. Level rates it ; you can apply on RBC.
Level's read on this job
- On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Python, Scala and Spark.
- Level classifies it as a lead role.
- Level lists 837 other open roles at RBC.
- The role was posted in the last few days.
AI in this role
Lead data scientist to develop and maintain machine learning models and data-driven transaction monitoring solutions for AML analytics.
Job Description
WHAT IS THE OPPORTUNITY?
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:TORONTOCity:
TorontoCountry:
CanadaWork hours/week:
37.5Employment Type:
Full timePlatform:
GROUP RISK MANAGEMENTJob Type:
RegularPay Type:
SalariedPosted Date:
2026-10-19Application Deadline:
2026-11-14Note: 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.
How we rate this
Lead Data Scientist, AML Analytics at RBC rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $170k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where aml was part of your work. What did you do?
- Tell me about a project where transaction monitoring was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: NLP, Machine learning, Data Analysis, Aml, and Transaction Monitoring. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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