Senior AML Data Scientist — ML & Risk Modeling

SoFi; Cottonwood Heights (UT); On-site; USD 150,000 - 210,000; Full time

Job summary

SoFi is seeking a Compliance Senior Data Scientist to advance AML model development, optimization and validation across multiple product lines. You will lead governance and reporting efforts, ensuring regulatory alignment and high-quality data for enterprise-wide risk coverage.

You will architect advanced models using machine learning and statistics, collaborate with AML governance, and deliver robust dashboards and MI reports for executives.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field.
• 3+ years in finance focusing on BSA/AML, OFAC, or fraud modeling/analytics.
• SQL and Python for predictive analytics.
• Knowledge of cloud computing and distributed processing.
• Experience leading AML governance initiatives and audits.
• Strong communication across business lines.

Responsibilities

• Develop, optimize, and validate AML models for risk-based screening.
• Maintain AML vendor solutions and monitor model performance.
• Research large data sets for data quality and suitability.
• Lead design of AML models using ML and statistics.
• Embed AML compliance in model development and deployment.
• Document methodology, data sources, and validation results.
• Create dashboards displaying AML metrics for leadership.
• Support governance, audits, and cross-functional reviews.

Skills

BSA/AML knowledge

SQL

Python

Data quality validation

Cloud computing

Distributed computing

Communication

Education

BSc or MSc in statistics/CS/math/finance/engineering

Tools

Tableau

DataDog

Monte Carlo

Snowflake

Terraform

Docker

Kubernetes

Job description

SoFi is seeking a Compliance Senior Data Scientist to advance AML model development, optimization and validation across multiple product lines. You will lead governance and reporting efforts, ensuring regulatory alignment and high-quality data for enterprise-wide risk coverage.

You will architect advanced models using machine learning and statistics, collaborate with AML governance, and deliver robust dashboards and MI reports for executives.