Title: AI/ML Engineer
Location: Onsite in Boston or Quincy or Burlington in Massachusetts -  4 days onsite
Duration: 12 months
Pay: 60-65

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, including precision, recall, and 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.
• Support development and testing teams by answering questions and updating documentation as needed based on feedback.
• Be responsible for communication, resolution, and potential escalation of critical issues.
• Work with the Project Manager and Product Owner to create and manage user stories using Jira.
• Support the 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 them in an understandable manner to stakeholders, developers, testers, and users at multiple levels.

• Experience with machine learning, advanced analytics, model development, evaluation, tuning, and monitoring.
• Strong hands-on data analysis and feature engineering experience using large transactional and reference datasets.
• Knowledge of AML, sanctions screening, transaction monitoring, alert prioritization, and financial crime analytics.
• Experience analyzing model performance, including precision, recall, false positives, false negatives, alert quality, drift, and data quality.
• Proficiency creating BRDs, data mapping documents, and user stories using Jira.
• Strong requirements gathering, documentation, problem-solving, and analytical skills.
• Experience working with cross-functional teams, including development, testing, data engineering, compliance, and operations.
• Experience supporting Agile delivery, UAT, testing, issue triage, resolution, and escalation.
• Ability to translate complex ideas and problems into clear business requirements and solutions and communicate them effectively to stakeholders at multiple levels.
• Ability to work independently in a complex, deadline-driven environment.