Product Manager

Anblicks

• $120K — $145K *
Dallas, TX 75217In-Person
Finance & Insurance
8 - 10 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data, Engineering, Business, or a related field.
  • 8+ years of experience in Data Product Management or Data & Analytics.
  • Proven experience in delivering enterprise-scale data platforms for financial crime solutions.
  • Strong understanding of data modeling, warehousing, and distributed systems.
  • Hands-on experience with SQL and BI tools like Power BI or Tableau.

Responsibilities

  • Define and drive the AML Monitoring Platform product vision and roadmap.
  • Establish a scalable data foundation for transaction monitoring.
  • Identify high-value use cases for AML detection and reporting.
  • Own the end-to-end delivery of the AML data product lifecycle.
  • Translate complex compliance needs into actionable product requirements.
  • Collaborate with engineering teams on scalable data pipelines and architecture.
  • Lead Agile delivery processes, managing trade-offs and tracking impact.

Benefits

  • Collaborate with diverse cross-functional teams.
  • Drive significant impact in the financial compliance landscape.
  • Work with modern data platforms like Snowflake and Azure.
  • Opportunity to influence decision-making at the leadership level.
Full Job Description
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
* Ladders Estimates

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