Product Manager

Define and drive the AML Monitoring Platform product vision, strategy, and multi-year roadmap. Establish a scalable, enterprise-grade data foundation for transaction monitoring and financial-crime detection Identify and prioritize high-value use cases (rule-based detection, anomaly detection, alert prioritization, regulatory reporting, AI/ML) Evangelize the AML platform vision across compliance, business, and leadership stakeholders Data Product Ownership Own end-to-end delivery of the AML data product lifecycle: Canonical, normalized transaction and party data models Detection rule engine and AML typology coverage Alert and case data feeding investigator workflows Risk scoring, segmentation, and entity relationship resolution Translate complex compliance and business needs into clear, actionable product and data requirements Define KPIs, success metrics, and product SLAs (e.g., detection coverage, false-positive rate, alert-to-case conversion, time-to-disposition) Cross-Functional Leadership Partner with senior stakeholders across: Compliance, Financial Crime, Investigations, Risk, and Business SMEs Data Engineering, Architecture, Governance, and Analytics/ML teams Act as a strategic bridge between business/compliance and technical organizations Influence decision-making at the leadership level Data Architecture & Engineering Collaboration Collaborate with engineering teams to design: Scalable data pipelines (ETL/ELT) across ingestion, curation, and detection layers Modern data architectures (medallion, lakehouse, warehouse) Batch, scheduled, and near-real-time processing capabilities Ensure alignment with enterprise data platforms (e.g., Snowflake, Azure, Databricks) and integration with downstream case-management systems Data Governance & Quality Drive data governance frameworks for AML data: Standard definitions, taxonomies, and metadata Data lineage, stewardship, and ownership Ensure data quality, consistency, auditability, and compliance with AML and privacy regulations Manage master data, entity resolution, and identity resolution strategies critical to accurate detection Analytics & Insight Enablement Enable advanced capabilities such as: Alert dashboards, investigator triage queues, and executive/regulatory reporting Detection-performance, typology-trend, and false-positive analysis Threshold calibration, peer-group benchmarking, and segmentation Partner with teams on AI/ML-driven use cases (e.g., anomaly detection, risk scoring, alert prioritization, model explainability) Execution & Delivery Lead Agile delivery (backlog prioritization, sprint planning, releases) Manage trade-offs across scope, timeline, and quality Track adoption, usage, and business impact; iterate continuously Required Qualifications Bachelor's or Master's degree in Computer Science, Data, Engineering, Business, or related field 8+ years of experience in: Data Product Management / Product Management / Data & Analytics Strong understanding of: Data modeling, data warehousing, and distributed data systems ETL/ELT pipelines and integration patterns Hands-on experience with: SQL and BI tools (Power BI, Tableau, Looker, etc.) Preferred Qualifications Experience with AML, transaction monitoring, fraud detection, KYC, or financial-crime compliance initiatives Familiarity with case-management and investigation systems Experience with modern data platforms: Knowledge of AML regulatory, data governance, privacy, and compliance frameworks (e.g., BSA, SAR/STR reporting, sanctions screening) Agile/Scrum certification or strong Agile delivery experience Strategic thinking with strong execution focus Deep data and analytics expertise Exceptional stakeholder management and executive communication Ability to influence without authority Strong problem-solving and decision-making skills #J-18808-Ljbffr Anblicks Inc.