Officer, AI/ML Compliance Technology Business Analyst

Officer, AI/ML Compliance Technology Business Analyst at State Street

We are actively seeking an Officer-level Compliance Technology Business Analyst / AI / Machine Learning professional to join our team. This pivotal role involves supporting the development and operation of data-driven solutions across our Anti-Money Laundering (AML), Sanctions Screening, and Financial Crimes Compliance platforms. This is a highly hands-on, data-science focused position, requiring direct engagement with large datasets, machine learning models, and analytics pipelines crucial for detecting and preventing financial crime.

The successful individual will act as a key liaison with project sponsors, stakeholders, external vendors, and various divisions within State Street. Responsibilities include documenting current state processes, eliciting, and documenting requirements to ensure the delivery of high-quality products. Candidates must demonstrate strong leadership in analysis, problem-solving, documentation, and communication. The role requires the ability to work with minimal direction while keeping senior management informed on all analytical deliverables.

The ideal candidate possesses robust quantitative and technical skills, a solid understanding of machine learning techniques, and a keen interest in applying AI within a regulated financial services environment. You will collaborate closely with senior data scientists, engineers, compliance partners, and technology teams to build, test, and monitor models, ensuring all solutions are explainable, auditable, and compliant with regulatory expectations.

What You Will Be Responsible For

As an Officer, AI/ML Compliance Technology Business Analyst, your key responsibilities will include:

• Developing, testing, and enhancing machine learning and advanced analytics models to support AML, sanctions screening, transaction monitoring, and alert prioritization.
• Performing hands-on data analysis using extensive transactional and reference datasets to identify patterns, anomalies, and risk indicators related to financial crime.
• Supporting feature engineering activities, including data exploration, feature selection, and transformation, to improve model performance and stability.
• Training, evaluating, and tuning models using appropriate techniques and performance metrics such as precision, recall, and false-positive reduction.
• Assisting in validating model outputs by analyzing false positives, false negatives, and alert quality in collaboration with compliance and operations teams.
• Contributing to comprehensive model documentation, including assumptions, methodologies, limitations, and performance results, to facilitate audit and regulatory review.
• Supporting ongoing model monitoring and performance tracking, identifying drift, degradation, or data quality issues, and recommending remediation strategies.
• Working with data engineering teams to understand data pipelines, resolve data issues, and ensure the accuracy and reliability of model inputs.
• Participating actively in Agile delivery processes, contributing to user stories, testing activities, and release support for AI/ML solutions.
• Supporting User Acceptance Testing (UAT) by validating model behavior against defined business and compliance expectations.
• Staying current with emerging AI/ML techniques, open-source tools, and industry trends relevant to financial crime and compliance analytics.
• Translating complex ideas into clear and cogent business requirements documents (BRDs).
• Proficiently creating BRDs and data mapping documents.
• Collaborating with cross-functional teams to identify requirements, provide guidance, and assist with resolving complex issues.
• Ensuring that any gaps identified in BRDs are addressed and rectified by the relevant teams.
• Supporting development and testing teams by answering questions and updating documentation based on feedback.
• Being responsible for communication, resolution, and potential escalation of critical issues.
• Working with Project Managers and Product Owners to create and manage user stories using Jira.
• Supporting the team in triaging issues identified during testing.
• Operating effectively in a complex, deadline-driven organization on projects with minimal supervision.
• Analyzing complex problems, deriving options and solutions, and presenting them understandably to stakeholders, developers, testers, and users across multiple levels.

What We Value

These skills are essential for success in this role:

• A strong foundation in machine learning and statistical concepts, including supervised learning, basic unsupervised techniques, and model evaluation.
• Hands-on experience with data analysis and modeling using tools such as Python and SQL.
• Experience working with large, complex datasets; exposure to financial or transactional data is highly advantageous.
• Understanding of common challenges in applied machine learning, such as data quality, class imbalance, and model interpretability.
• Interest in or exposure to AML, sanctions, fraud, or risk analytics, particularly within regulated environments.
• Ability to clearly explain analytical results and model behavior to both technical and non-technical stakeholders.
• Strong problem-solving skills, meticulous attention to detail, and a structured, analytical mindset.
• Ability to work collaboratively within cross-functional teams and learn from senior data scientists and engineers.
• Familiarity with Agile delivery practices and version-controlled development environments is preferred.
• Curiosity, eagerness to learn, and strong motivation to grow as a data scientist within the compliance and financial crime domain.
• Ability to manage multiple simultaneous tasks effectively in a high-pressure, deadline-driven environment.
• Ability to take ownership and initiative, negotiate, influence, build consensus, and successfully navigate a demanding, international environment.
• Strong skills in analytical thinking, problem-solving, research, time management, and verbal and written communication.
• Strong collaboration and relationship management skills.
• Ability to work independently.

Education & Preferred Qualifications

• Bachelor’s degree with a concentration in Engineering, Business, or Technology is preferred.
• Candidate should have 1-2+ years of experience in financial services, including relevant responsibilities.
• Experience in the financial domain is required, with knowledge of Anti-Money Laundering (AML), Sanctions, Transaction Monitoring, Know Your Customer (KYC), financial securities, and trading principles.
• Experience in FinTech working with SWIFT message types (specifically Swift - MT, MX message formats).
• Experience in FinTech working with Fedwires transactions.
• Experience/Exposure to Financial Crimes Compliance, such as AML and Alert generation.
• Knowledge of LexusNexus Firco Continuity or any other AML products is preferred.
• Experience with JIRA, Agile (Epics, Stories, working in Kanban team).
• Good understanding of Agile methodology and Agile Ceremonies.
• Ability to work with geographically distributed teams while maintaining the highest standards in collaboration and communication across QA/DEV and Business teams.
• Team-oriented attitude.
• Excellent verbal and written communication skills.
• Must be self-motivated, self-driven, and accountable for the timely completion of deliverables.
• Strong problem-solving skills with great attention to details.

Key skills/competency

• Machine Learning
• Data Analysis
• AML Compliance
• Sanctions Screening
• Financial Crime
• Python
• SQL
• Agile Methodology
• Model Validation
• Regulatory Compliance