The Role
Lead the vision, strategy, roadmap, and delivery of an enterprise AML monitoring data platform. Own transaction and party data models, detection rules, alert and case data, risk scoring, governance, quality, analytics, and AI/ML use cases. Partner with compliance, investigations, risk, data engineering, architecture, governance, and analytics teams to define requirements, manage Agile delivery, establish metrics, and improve detection performance, adoption, and business impact.
Summary Generated by Built In
Key Responsibilities
Product Leadership & Strategy
- 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
- Proven experience delivering enterprise-scale data platforms or financial-crime / AML / transaction-monitoring solutions
- 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:
- Snowflake, Azure Data Platform
- 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
Key Competencies
- 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
- Risk-aware, compliance-centric mindset
Skills Required
- Bachelor's or Master's degree in Computer Science, Data, Engineering, Business, or a related field
- 8+ years of experience in data product management, product management, or data and analytics
- Experience delivering enterprise-scale data platforms or financial-crime, AML, or transaction-monitoring solutions
- Strong understanding of data modeling, data warehousing, and distributed data systems
- Experience with ETL/ELT pipelines and integration patterns
- Hands-on experience with SQL and BI tools such as Power BI, Tableau, or Looker
- 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 such as Snowflake and Azure Data Platform
- Knowledge of AML regulatory, data governance, privacy, and compliance frameworks, including BSA, SAR/STR reporting, and sanctions screening
- Agile/Scrum certification or strong Agile delivery experience
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
