Senior AML Data Scientist: ML for Financial Crime

SoFi; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

SoFi in San Francisco seeks a Compliance Senior Data Scientist to advance the AML program through model development, optimization, validation, governance, and MI reporting across banking, brokerage and lending lines.

Role involves designing advanced AML models using ML, validating data quality, and ensuring regulatory alignment with governance across the model lifecycle. Collaboration with AML governance and cross-functional teams is essential.

Qualifications

• Bachelor’s or Master’s Degree in Statistics, Computer Science, Mathematics, Finance, Engineering or related fields.
• 3+ years in finance focusing on BSA/AML, OFAC or fraud analytics.
• Strong SQL and Python for predictive modeling and data validation.
• Experience with databases, cloud computing and distributed systems.
• Experience leading AML governance initiatives and audits.
• Effective communication across all business lines.

Responsibilities

• Facilitate AML model development, implementation and validation across customer screening, transaction monitoring and risk scoring.
• Maintain and test AML vendor solutions for performance and design integrity.
• Architect and lead advanced AML models using ML and statistics.
• Ensure AML compliance is embedded in model design and governance.
• Document methodologies, data sources and validation results.

Skills

SQL

Python

AML governance

Data quality

Education

Bachelor’s/Master’s in relevant field

Tools

Tableau

Snowflake

Docker

Kubernetes

Terraform

LexisNexis

Verafin

Job description

SoFi in San Francisco seeks a Compliance Senior Data Scientist to advance the AML program through model development, optimization, validation, governance, and MI reporting across banking, brokerage and lending lines.

Role involves designing advanced AML models using ML, validating data quality, and ensuring regulatory alignment with governance across the model lifecycle. Collaboration with AML governance and cross-functional teams is essential.