We are seeking an AVP-level Compliance Technology Business Analyst with expertise in AI and machine learning to join our dynamic team focused on developing data-driven solutions for Anti-Money Laundering (AML), Sanctions Screening, and Financial Crimes Compliance. This hands-on role involves working closely with large datasets and analytics pipelines to detect financial crime, requiring strong quantitative skills and a deep understanding of machine learning techniques. The ideal candidate will develop, test, and enhance models while ensuring they are explainable and compliant with regulatory standards. Key responsibilities include data analysis, feature engineering, model validation, documentation, and collaboration with cross-functional teams using tools like Python, SQL, Jira, and Agile methodologies. Experience in the financial domain, particularly AML and sanctions compliance, is essential, along with proficiency in handling complex datasets and a keen interest in applying AI in regulated environments.
Skills
Python
SQL
Jira
Agile
AML
Sanctions Screening
Financial Crimes Compliance
Machine Learning
Data Analysis
Feature Engineering
Model Evaluation
User Acceptance Testing
BRDs
Data Mapping Documents
SWIFT
Messaging Formats
Fedwire Transactions
LexisNexus Firco Continuity
What you'll do
Develop, test, and enhance machine learning models for AML, sanctions screening, and transaction monitoring.
Perform data analysis using large datasets to identify patterns and risk indicators related to financial crime.
Support feature engineering activities by exploring, selecting, and transforming data to improve model performance.
Train, evaluate, and tune models using appropriate techniques and metrics to ensure high accuracy and reliability.
Assist in validating model outputs by analyzing false positives/negatives with compliance teams.
What we're looking for
5+ years of experience in financial services with focus on AML, sanctions, transaction monitoring.
Strong foundation in machine learning techniques and statistical concepts.
Hands-on experience with Python and SQL for data analysis and modeling.
Experience working with large, complex datasets, especially financial or transactional data.
Understanding of challenges in applied machine learning, including model interpretability and data quality issues.
Ability to clearly communicate analytical results and model behavior to both technical and non-technical stakeholders.
Familiarity with Agile delivery practices and JIRA for project management.
Market check
Salary context
This
$80,000–$140,000
range sits above
2%
of similar postings on FindRole.
Peer median band
$155,560–$234,150
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$161,250–$231,862
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About State Street
State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody
State Street currently has
133 open roles
on FindRole.
Listed pay typically runs
$110,000–$180,000
across 131 roles with salary data.
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