Senior AML Business Data Manager, Transaction Monitoring Platforms

Work Location: Mount Laurel, New Jersey, United States of America Hours: 40 Pay Details:

$122,304 – $199,680 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate’s skills and experience, job‑related knowledge, geographic location, and other specific business and organizational needs. As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role. Line of Business: Analytics, Insights, & Artificial Intelligence Job Description: Department Overview: The Senior AML Business Data Manager for AML Data is responsible for supporting implementation, enhancement and maintenance of AML typologies. This includes design, build and maintenance of Transaction Monitoring Models based on the analysis of transaction, account and customer data for various financial services and products. Identification and analysis of potential transaction monitoring typologies and risks for the detection of AML suspicious activity in alignment with policies, standards, and procedures and oversight of transaction monitoring systems will be part of the responsibilities assumed. The Senior AML Business Data Manager for AML Data is accountable for coordination with technology and data teams on planning for scenario tuning, defect prioritization and management, integration with third party systems and external controls. Our team currently operates under a primarily off‑site model, with employees expected to work in the office for “Moments that Matter” at a frequency determined by the business line. Candidates that live within a 50 mile radius of selected TD AML hub locations is strongly preferred. Preferred Skills & Experience : 10+ years of previous experience as a Subject matter expert (SME) for AML Transaction Monitoring systems (e.g., SAS, Actimize, Oracle, BAE, etc.), with a deep understanding of how they work, including data segmentation, data flows, Above-the-Line/Below-the-Line tuning for scenario thresholds, and associated troubleshooting. Solid understanding of AML Transaction Monitoring and other financial crime compliance regulations and industry best practices. Solid understanding of data workflows from ingestion to reporting and develop strategies to optimize system configurations, minimize false positives and enhance detection capabilities through segmentation and tuning efforts. Previous experience as the central point of contact, coordinating between Transaction Monitoring, IT and Data teams to ensure timely project delivery and system performance in a fast‑paced work environment. Ability to work closely with stakeholders to assess upgrades, or system enhancements. Ensure compliance with agreed‑upon deliverables and SLA. Depth & Scope: Delivers advanced analytical capabilities above and beyond existing methods Exceptionally leads and runs analytical projects autonomously and creates and effectively delivers analytical presentations for executive audiences/stakeholders Showcases advanced level peer leadership, impacts and influences partner, and may mentor/coach peers Extensive understanding of the business supported and the overall bank with deep expertise and highly specialized knowledge of analytical concepts and techniques Acts as a key business partner, guides and collaborates with business leaders to prioritize and identify key business needs and provides impactful analytical insights Education & Experience: Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science) Graduate’s degree preferred with either progressive project work experience, or; 7+ year of relevant experience; higher degree education and research tenure can be counted Customer Accountabilities: Works closely with business owners to identify opportunities and serves as an ambassador for data science Is familiar with the business context and data infrastructure and can translate business problems to viable data science solutions Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract insights from the big data Visualizes insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision‑makers and stakeholders at every level of technical understanding Collaborates with other partners, such as data and business analysts, software engineers, data engineers, and application developers to develop scalable and sustainable data science solutions that retains long term benefit to the business Provides deep technical leadership and expertise to support and define future direction in one or more specialized areas or leads strategic development efforts on new or emerging data science related projects Plays a lead role on cross functional teams of data scientists, data analysts, data engineers, and business process owners to build cutting edge analytic solutions Shareholder Accountabilities: Provides analytical thought leadership and stays current on developments in data mining and the application of data science Provides thought leadership and/or broad industry knowledge across multiple business/functional areas or across the enterprise Applies industry/analytical expertise to provide innovative and sound solutions that increases business results and/or minimizes risk Identifies new analytical trends/data needs and repeatable analytic solutions and works with stakeholders to generate hypothesis and creates analytical models that help answer impactful business questions Protects the interests of the organization – identifies and manages risks, and escalates non‑standard, high‑risk activities as necessary Accountable for creating and implementing processes and systems to extract knowledge or insights from data of various forms either structured or unstructured Employs techniques and theories drawn on many fields within the broad areas of mathematics and statistics #J-18808-Ljbffr TD Bank Group