Product Manager

Anblicks Inc.; Dallas, Northern (TX, KY); Hybrid; USD 130,000 - 170,000; Full time

Job summary

Anblicks Inc. in Dallas, TX is seeking a senior Data Product Manager to define the AML monitoring platform vision, strategy, and multi-year roadmap.

You will own end-to-end data product delivery for transaction monitoring and regulatory reporting, driving scalable data foundations and a high-value use-case roadmap. You will partner with Compliance, Investigations, Risk, and Data Engineering teams to translate complex AML needs into concrete data requirements, KPIs, and actionable product plans,

Qualifications

• 8+ years in Data Product Management, PM, or Data & Analytics.
• Strong skills in data modeling, warehousing, and distributed data systems.
• Experience with ETL/ELT pipelines and data integration patterns.
• Proficient in SQL and BI tools such as Power BI, Tableau, Looker.

Responsibilities

• 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.

Skills

Data product mgmt

Data modeling

ETL/ELT

Education

BS/MS in CS/Data/Engineering/Business

Tools

SQL

Power BI

Tableau

Looker

Job description

• 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