Senior Data Scientist (10+ years) to build AML transaction monitoring solutions using Python, and SQL 58574 Our financial services client is seeking a Senior Data Scientist (10+ years) to build AML transaction monitoring solutions using Python, and SQL58574 Join a leading financial institution supporting a recent AML transaction monitoring initiative within a data analytics environment. This role focuses on analytical activities related to transaction monitoring systems, including data quality checks, customer segmentation, threshold setting, and model performance monitoring across Oracle and Azure platforms. The position offers exposure to large-scale datasets and collaboration with multiple business teams on data-driven initiatives.

Contract, Hybrid Hybrid: Hybrid-3 days a week in office 10+ years in Data Science and Data Analytics environments ~ Expert-level proficiency in Python and SQL ~ Large-scale dataset analysis using statistical techniques and data mining tools ~ Master’s degree preferred in computer science, data science,



statistics, or related field Experience with SAS, Informatica, Tableau, and other relevant data analytics tools AML knowledge Conduct analytical activities related to AML transaction monitoring systems Provide analysis, design, and support for technical data management solutions across projects Perform data quality checks on raw and curated data within Oracle and Azure platforms Execute customer segmentation, initial threshold setting, and model performance monitoring activities Maintain structured documentation supporting scenario review programs for audit, compliance, and regulatory requirements Execute quality control procedures for interim monitoring solutions and identify implementation gaps Collaborate with business teams to identify improvement opportunities using supporting data and models Disclaimer: AI may be used in evaluating candidates.

📌 Senior Data Scientist (10+ years) to build AML transaction monitoring solutions using Python, and SQL 58574 (Toronto)
🏢 S.i. Systems
📍 Toronto