Decompose high-level features / requirements into user stories, acceptance criteria, and clear backlog prioritization.
Collaborate with engineering, data science, and solutions teams to deliver high-quality TM features (real-time and batch pipelines, detection analytics, alert scoring, alert/ case creation, feedback loops).
Drive backlog grooming, sprint planning, and manage priorities / dependencies across multiple engineering pods.
Participate in design reviews, technical estimation, and ensure non-functional requirements (performance, scalability, security, auditability) are included in scope.
Support calibration, back-testing, champion / challenger model assessment, model/ rule threshold tuning, monitoring of false positives / recall and improving true positive detection.
Ensure explainability, reason codes, lineage, and model transparency across TM solution, including detection analytics and alert / risk scoring modules.
Work with engineering teams and customers to define test cases, regression test suites, and oversee UAT / release validation.
Monitor metrics (alert volumes, false positives, investigator throughput, conversion rates) and iterate to optimize.
Manage dependencies with external systems (watchlists, screening, sanctions feeds, data enrichment, client data ingestion).
Create or update product documentation, user guides, runbooks, and support internal teams (sales, services, support).
Stay current on AML regulations, typologies and trends across the financial crime sector.
Requirements
6+ years of experience in product, business analysis, or domain roles, with at least 4 years working in AML / financial crime / risk / compliance products or operations.
Deep understanding of AML transaction monitoring, financial crime typologies and risks. Understands case management flows and regulatory expectations.
Experience working on systems that handle regulated, mission-critical workflows (auditability, traceability, security).
Familiarity with data processing and analytics: pipelines, feature engineering, model scoring, streaming vs batch.
Comfortable crafting user stories, acceptance criteria, and working in Agile / Scrum methodologies.
Strong stakeholder management skills: able to mediate between compliance, operations, engineering, and clients.
Excellent written and verbal communication; capable of explaining technical & domain complexity to business and technical audiences.
Analytical mindset, with data-driven decision making and ability to measure outcomes.
Degree in Computer Science, Engineering, Data Science, or equivalent; or extensive domain equivalent experience.
CAMS or equivalent certification is preferred
Benefits
Healthcare cover through the VHI
Company pension contribution
Life assurance/ Income protection
23 days annual leave
3 company closure days
Annual bonus opportunity
Work From Home set-up allowance
Opportunity to work with clients and colleagues on a global scale for a world leader in Client Lifecycle Management
Other competitive company benefits, such as flexible working hours, work from home policy, bike to work scheme, sports and social committee, weekly fitness and sports classes and much more
Buddy system for all new starters
Collaborative working environment
Extensive training programs, classroom and online, through ‘Fenergo University’
Opportunity to work on a cutting-edge Fintech Product, using the latest of tools and technologies
Defined training and role tracking to allow you see and assess your own career development and progress.
Active sports and social club
State of the art offices in the heart of Dublin’s Docklands with great facilities, canteen and games area