AML Business Systems Analyst / Consultant

the Client•Chicago, IL

21h•Hybrid

About The Position

The AML Business Systems Analyst / Consultant will support, maintain, enhance, and optimize AML systems and processes across transaction monitoring, customer risk rating, screening, data validation, reporting, and system operations. This role sits within the U.S. AML Transformation, Delivery & Insights team, which supports the U.S. Anti-Money Laundering organization through AML systems, technology enablement, reporting, business intelligence, data governance, and operational support. The group is responsible for maintaining and enhancing AML platforms, supporting transaction monitoring, customer risk rating, sanctions/screening processes, data quality initiatives, and regulatory reporting requirements. The individual will serve as a key SME for SAS Viya and related AML platforms, supporting system functionality, issue triage, release management, defect resolution, testing, integrations, and operational improvements. The role will also support major initiatives connecting Technology, Data, Reporting, and AML business teams. This is a contract-to-hire engagement with a very high likelihood of permanent conversion, offering significant ownership of SAS Viya and AML platform capabilities and broad stakeholder exposure across AML, Technology, Reporting, Data Governance, and Business teams.

Requirements

Strong hands-on expertise in SAS Viya AML, advanced SQL, SAS reporting tools, SAS Visual Analytics, data pipelines, and analytical data models.
Strong stakeholder management and relationship-building skills.
Excellent verbal and written communication skills.
Ability to bridge business and technical teams effectively.
Strong analytical and problem-solving abilities.
Ability to challenge existing processes and recommend improvements.
Strong organizational and documentation skills.
Collaborative leadership style.
Ability to manage competing priorities in a fast-paced AML environment.
Detail-oriented with a strong focus on controls, quality, and operational excellence.
7 years of BSA/AML reporting, analytics, data governance, or financial crimes experience, including 5 years leading AML reports.
Strong experience supporting AML technology platforms and system delivery functions.

Nice To Haves

SAS Studio
SAS Visual Analytics
Python
Power BI
Tableau
SharePoint
Agile / SDLC methodologies
Process mapping and workflow design
Data governance and reporting experience
Automation and process optimization experience
Banking regulatory and compliance technology experience

Responsibilities

Support AML systems including SAS Viya, transaction monitoring, customer risk rating, and screening platforms.
Triage production issues, system defects, data quality concerns, and business process questions.
Lead data validation, reconciliations, documentation activities, and testing efforts related to system enhancements.
Investigate SAS Viya functionality and challenge existing processes to identify improvement opportunities.
Develop testing strategies, test plans, test cases, and coordinate test execution.
Connect and lead Technology, Data, Transaction Monitoring Rules, and Reporting teams on major initiatives.
Serve as the SME for SAS Viya functionality, workflows, and AML use cases.
Recommend, design, and support solutions within SAS Viya to improve AML processes.
Support development of process maps, workflow models, and system interaction documentation.
Create and maintain job aids, operational documentation, and data validation procedures.
Partner with AML, Technology, Reporting, Data Governance, and business teams to support releases, upgrades, workflow enhancements, and platform improvements.
Drive automation of reports and processes to improve efficiency, controls, and transparency.
Lead end-to-end AML reporting, dashboards, and insights for management, exam, and AML operational functions.
Own reporting requirements, data sourcing, calculation logic, QA/QC, reconciliations, controls, approvals, releases, production monitoring, and issue remediation.
Establish strong data governance, including definitions, data dictionaries, lineage, data quality monitoring, documentation, retention, and audit-ready evidence.
Lead analysts and matrixed resources while partnering effectively with AML, Technology, vendors, and senior stakeholders.