Senior Data Scientist

About the role

The Compliance Senior Data Scientist will assist the Anti-Money Laundering Compliance program with various tasks including model development, optimization, validation, and governance.

Responsibilities

• Facilitate AML model development, implementation, optimization, assessment, and validation of risk-based customer screening, transaction screening, transaction monitoring, and AML customer risk rating across multiple product lines.
• Maintain, test, and configure AML vendor solutions to ensure conceptual soundness, proper implementation, and acceptable model performance.
• Research, compile, and evaluate large datasets to assess quality, integrity, and completeness for AML model development.
• Architect and lead the design of advanced AML models using machine learning and statistical modeling methods for supervised and unsupervised learning.
• Document modeling methodology, data sources, assumptions, and validation results.
• Lead governance and quality control across the AML model lifecycle, including code reviews, validation of methodology, input data integrity, and performance metrics.
• Ensure adherence to the organization's established ML framework, coding conventions, documentation standards, and model risk management policies, embedding AML compliance and regulatory requirements into design and deployment.
• Oversee documentation and review processes for internal model validation, external regulatory examinations, and cross-functional approvals, while supporting resolution of development blockers and coordinating with key stakeholders.
• Develop robust management information dashboards displaying real-time or near real-time AML metrics.
• Partner with and advise the AML Governance Unit by providing necessary data for AML Risk Assessments, internal/external audit examinations, and other regulatory requirements.

Requirements

• Bachelor’s Degree or Master’s Degree in Statistics, Computer Science, Mathematics, Finance, Computer Science, Engineering, or other relevant areas.
• 3+ years of experience in the finance industry focusing on BSA/AML, OFAC, or fraud modeling/analytics.
• Statistical/data analytical skills, including data quality validation, and predictive modeling experience in SQL and Python.
• Knowledge of and ability to leverage traditional databases, cloud-based computing, and distributed computing.
• Track record of leading AML governance-related initiatives, such as risk assessments, internal/external audits, and other regulatory requirements.
• Demonstrated ability to communicate effectively with all levels of the organization and across different business lines.

Qualifications

• None specified

Skills

• Machine Learning
• Statistical Modeling
• Data Visualization
• Data Monitoring Systems
• Cloud Data Infrastructure
• Automated Transaction Monitoring
• Customer/Transaction Screening
• Infrastructure Automation Software
• Containerization
• Container Orchestration
• CAMS Certification (preferred)

Benefits

To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!