Artificial Intelligence & Machine Learning, Off (US Only)

About the role

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.

Responsibilities

• 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.
• Support User Acceptance Testing (UAT) by validating model behavior against business and compliance expectations.
• Stay current on emerging AI/ML techniques, open-source tools, and industry trends relevant to financial crime and compliance analytics.
• Translate complex ideas into cogent business requirements documents.
• Create BRDs and data mapping documents.
• Collaborate with cross-functional teams to identify requirements, provide guidance, ask and respond to questions, and assist with resolving complex issues.
• Ensure that any gaps identified in the BRD are addressed and rectified by the relevant team.
• Answer questions and update documentation as needed based on feedback.
• Work with the Project Manager and Product Owner to create and manage user stories using Jira.
• Support team in triaging issues found during testing.
• Work in a complex, deadline-driven organization on projects with minimal supervision.
• Analyze complex problems, derive options and solutions, and present in an understandable manner to stakeholders, developers, testers, and users at multiple levels.

Qualifications

• 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 a strong plus.
• 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 in regulated environments.
• Ability to clearly explain analytical results and model behavior to technical and non-technical stakeholders.
• Strong problem-solving skills, attention to detail, and a structured, analytical mindset.
• Ability to work collaboratively in cross-functional teams and learn from more senior data scientists and engineers.
• Familiarity with Agile delivery practices and version-controlled development environments is preferred.
• Curiosity, eagerness to learn, and motivation to grow as a data scientist within the compliance and financial crime domain.
• Ability to manage multiple simultaneous tasks in a high-pressure, deadline environment.
• Ability to take ownership and initiative, to negotiate, influence, and build consensus and successfully navigate within a demanding and 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.

Preferred Qualifications

• Bachelor’s degree with concentration in Engineering, Business or Technology preferred.
• Candidate should have 1-2+ years of experience in financial services, including relevant responsibilities.
• Experience in Financial domain is required: 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/Exposure to Financial Crimes Compliance - such as AML, Alert generation.
• Knowledge with LexusNexus Firco Continuity or any other AML products is preferred.
• Experience with JIRA, Agile (Epics, Stories, Working in Kanban team).
• Experience with Agile methodology and Agile Ceremonies.
• Team-oriented attitude.
• Excellent verbal and written communication skills.
• Self-motivated, self-driven, own and consider him/herself accountable for timely completion of deliverables.
• Strong problem-solving skills with great attention to details.