Data Scientist – Python/AML

Role overview

A financial-services client is seeking a Data Scientist focused on anti-money-laundering transaction monitoring. The contract role leads analytical work around scenario performance, predictive models and risk scoring, helping improve detection effectiveness while keeping monitoring approaches aligned with audit, regulatory and internal compliance expectations.

Responsibilities

• Lead analytics for AML transaction-monitoring scenarios and models.
• Maintain and optimize scenarios, queries and risk-detection logic.
• Run and monitor machine-learning models and tune performance.
• Build statistical and ML approaches for risk scoring and customer-behaviour analysis.
• Document model and monitoring work for audit and regulatory requirements.
• Collaborate with global AML teams to resolve monitoring issues and improve processes.

• Strong predictive-model and machine-learning experience.
• Python, PySpark, Databricks, Azure and SQL.
• Strong data exploration, statistics and problem-solving skills.
• Ability to communicate analytical work clearly and collaborate across teams.
• AML, banking, Java/Scala/Tableau or relevant technical certifications are assets.

Current BeachHead Job 20584 was posted October 9, 2026 in Toronto and is described as a current or anticipated vacancy. The individual page contains the complete application form and is used directly by RBB.