Strategic Leader - AML Modeling & Client Risk Analytics

Scotiabank; Toronto; On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Performance bonus

Employee Share Ownership Program

Pension Plan Matching

Health benefits from day one

Job summary

Scotiabank seeks a Senior Manager to lead AML Client Risk Rating model development and analytics. You will guide data scientists and partners, oversee documentation and governance, and ensure compliance with regulatory standards across AML programs.

Responsibilities include designing and enhancing CRR models, applying ML and statistical methods, and communicating findings to senior stakeholders in a regulated environment. Hybrid collaboration is common.

Qualifications

• Degree in STEM/Analytics or related field; advanced degree preferred.
• Extensive modeling, data science, ML, and risk analytics experience.
• Experience communicating model concepts to leadership and non-technical audiences.

Responsibilities

• Lead design, development, and maintenance of AML Client Risk Rating models.
• Oversee modeling techniques from statistics to AI/ML for risk-based ratings.
• Provide guidance to data scientists and cross-functional partners.
• Document model methodology, results, and governance evidence.
• Collaborate with Validation, Audit, Technology, Data, Privacy, Compliance.

Skills

Python programming

SQL querying

Data science methods

Machine learning

Statistical modelling

Model governance

Regulatory risk

Stakeholder management

Team leadership

Communication skills

Education

Bachelor's degree in STEM/Analytics

Master's degree preferred

Tools

Hadoop

Spark

BigQuery

TensorFlow / Keras / PyTorch

GCP

Linux

Git

Job description

Scotiabank seeks a Senior Manager to lead AML Client Risk Rating model development and analytics. You will guide data scientists and partners, oversee documentation and governance, and ensure compliance with regulatory standards across AML programs.

Responsibilities include designing and enhancing CRR models, applying ML and statistical methods, and communicating findings to senior stakeholders in a regulated environment. Hybrid collaboration is common.