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

• 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.

Skills

• Knowledge of AML regulations and the USA PATRIOT Act.
• Familiarity with regulatory guidance on Model Risk Management (Federal Reserve SR Letter 11-7, OCC Bulletin 2011-12, FDIC FIL 22-2017, DFS504).
• Experience with data visualization (e.g., Tableau).
• Experience with data monitoring systems (e.g., DataDog, Monte Carlo).
• Experience with cloud data infrastructure (e.g., Snowflake).
• Experience with automated transaction monitoring (e.g., Verafin).
• Experience with customer/transaction screening (e.g., LexisNexis).
• Experience with infrastructure automation software (e.g., Terraform).
• Familiarity with virtualization and containerization (e.g., Docker).
• Familiarity with container orchestration (e.g., Kubernetes).
• CAMS certification preferred.

Benefits

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