Sanctions Model Design AVP — ML & Risk Steward

State Street; Princeton (NJ); Hybrid; USD 80,000 - 140,000; Full time

Job summary

State Street seeks an AVP Sanctions Analyst to lead design, validation, and ongoing governance of sanctions screening models within the FCC framework. You will collaborate with FCC Technology, IT, and Model Risk Governance to ensure robust performance and compliance.

The role emphasizes quantitative analysis, ML/NLP techniques, and data enrichment, with responsibility for model reviews, upgrades, and risk assessment in a hybrid office setting.

Qualifications

• Degree in Data Science, CS, Statistics, Engineering, Finance or related field.
• Strong quantitative and analytical skills with hands-on proficiency in ML/NLP or related analytics.
• Proficiency in Python and SQL for data analysis, model evaluation, and automation.
• Experience with sanctions screening applications, models, and model risk management.

Responsibilities

• Act as owner of sanctions screening models, coordinating with FCC and IT.
• Monitor model performance, thresholds, and tuning; partner with tech teams on remediation.
• Support data quality, list management, and model configuration for sanctions screening.
• Lead annual reviews, validations, and MRM calendar activities.

Skills

Python

SQL

Machine Learning

NLP

Data Analysis

Model Risk Governance

Education

Bachelor's or Master's in Data Science or related field

Tools

Databricks

pandas

NumPy

scikit-learn

Job description

State Street seeks an AVP Sanctions Analyst to lead design, validation, and ongoing governance of sanctions screening models within the FCC framework. You will collaborate with FCC Technology, IT, and Model Risk Governance to ensure robust performance and compliance.

The role emphasizes quantitative analysis, ML/NLP techniques, and data enrichment, with responsibility for model reviews, upgrades, and risk assessment in a hybrid office setting.