AVP, Sanctions Modeling & Model Risk Management

State Street; Quincy (MA); Hybrid; USD 80,000 - 140,000; Full time

Benefits offered by this job

401K with company match

Comprehensive benefits

Paid time off

Job summary

State Street is seeking a Sanctions Analyst, AVP – Sanctions Model Design & Model Risk Management to join its Financial Crimes Compliance organization. The role focuses on sanctions screening models, quantitative analysis, and MRM lifecycle activities, with collaboration across FCC Technology, IT, and governance teams.

The ideal candidate has hands-on experience with enterprise sanctions platforms, strong Python and SQL skills, and the ability to lead model reviews, upgrades, and annual

Qualifications

• 6+ years of experience in financial crime compliance, sanctions screening, data science, quantitative analytics, or model risk management.
• Design, review, validate, and operate sanctions screening applications and models.
• Strong Python and SQL skills for data analysis and automation.
• Experience with AI/ML techniques and NLP in sanctions contexts.
• Ability to communicate complex analyses to senior stakeholders.

Responsibilities

• Act as a key liaison between FCC and IT for day-to-day sanctions screening model ownership.
• Monitor model performance, thresholds, and tuning parameters; coordinate remediation.
• Lead upgrades, calibrations, and validation across screening platforms.
• Evaluate NLP/ML techniques to improve alert generation and prioritization.
• Draft and maintain MRM documentation; present findings to governance forums.

Skills

Python

SQL

NLP

Machine Learning

Sanctions screening

Model risk management

Stakeholder communication

Education

Bachelor’s/Master’s in Data Science / CS / Statistics / Engineering / Finance

Tools

Databricks

pandas

NumPy

scikit-learn

SQL

Job description

State Street is seeking a Sanctions Analyst, AVP – Sanctions Model Design & Model Risk Management to join its Financial Crimes Compliance organization. The role focuses on sanctions screening models, quantitative analysis, and MRM lifecycle activities, with collaboration across FCC Technology, IT, and governance teams.

The ideal candidate has hands-on experience with enterprise sanctions platforms, strong Python and SQL skills, and the ability to lead model reviews, upgrades, and annual