Artificial Intelligence & Machine Learning, Off US Only - State Street

We are looking for an Officer ‑ level Compliance Technology Business Analyst / AI / Machine Learning professional to support the development and operation of data ‑ driven solutions across Anti ‑ Money Laundering (AML), Sanctions Screening, and Financial Crimes Compliance platforms. This role is highly hands ‑ on and data ‑ science focused, working directly with large datasets, machine learning models, and analytics pipelines used to detect and prevent financial crime.

Individual will liaise with the project sponsors, stakeholders, external vendors and other divisions within State Street to document current state, elicit & document requirements to ensure the delivery of quality products. Individual must demonstrate leadership abilities in analysis, problem solving, documentation and communication. Individual must be able to work under minimal direction while keeping senior management apprised of issues relating to analysis work related deliverables.

The ideal candidate has strong quantitative and technical skills, a solid understanding of machine learning techniques, and an interest in applying AI in a regulated financial services environment. The individual will work closely with senior data scientists, engineers, compliance partners, and technology teams to build, test, and monitor models while ensuring solutions remain explainable, auditable, and compliant with regulatory expectations.

What you will be responsible for

As Compliance Tech. AI/Machine Learning you will

• Develop, test, and enhance machine learning and advanced analytics models supporting AML, sanctions screening, transaction monitoring, and alert prioritization.
• Perform hands‑on data analysis using large transactional and reference datasets to identify patterns, anomalies, and risk indicators related to financial crime.
• Support feature engineering activities, including data exploration, feature selection, and transformation to improve model performance and stability.
• Train, evaluate, and tune models using appropriate techniques and performance metrics (e.g., precision, recall, false‑positive reduction).
• Assist in validating model outputs by analyzing false positives, false negatives, and alert quality in partnership with compliance and operations teams.
• Contribute to model documentation, including assumptions, methodologies, limitations, and performance results, to support audit and regulatory review.
• Support ongoing model monitoring and performance tracking, identifying drift, degradation, or data quality issues and recommending remediation.
• Work with data engineering teams to understand data pipelines, resolve data issues, and ensure model inputs remain accurate and reliable.
• Participate in Agile delivery processes, contributing to user stories, testing activities, and release support for AI/ML solutions.