Jobs · Engineering · Washington

Senior Data Scientist

SoFi · Seattle, WA · Today
EngineeringFull-time

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.
  • Ensure AML compliance and regulatory requirements are embedded in the model design.
  • Document modeling methodology, data sources, assumptions, and validation results.
  • Lead governance and quality control across the full 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 governance documentation related to tuning efforts, parameter changes, and data validation for AML transaction monitoring to maintain a comprehensive audit trail.
  • Track and report results of tuning and optimization activities and model performance to senior management.
  • 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!

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