Omits Financial & Technology Services Inc. is a licensed financial technology company specializing in secure cross-border payment solutions, multi-currency foreign exchange (FX) services, and digital wallet functionality.

We enable fast, safe, and transparent money transfers for individuals and businesses globally, supported by robust, automated KYC/AML compliance systems and a strong regulatory framework.

• Location: Remote (Nigeria preferred)
• Duration: 3-month contract (₦600,000/month)
• Potential: Full-time conversion post-launch

We are building a next-generation cross-border payments platform and are seeking an engineer to design and implement our end-to-end transaction monitoring and financial crime detection system.

This is not a traditional machine learning role.

You will be responsible for building a production-grade transaction monitoring engine that combines:

• Rules-based detection (regulatory foundation)
• Real-time risk scoring
• Behavioral analytics and machine learning (layered on top)

The system will be:

• Real-time and highly scalable
• Fully explainable and audit-ready
• Modular and capable of operating as a standalone platform

You will work closely with Engineering and Compliance to translate AML/CFT requirements into a robust, regulator-grade system.

• Design and implement the core monitoring system for both real-time and batch transaction analysis
• Develop a rules-based detection framework, including:
  • Velocity monitoring
  • Structuring detection
  • High-risk geography controls
  • New account and onboarding risk patterns
• Ensure all rules are configurable, version-controlled, and fully auditable

• Build a real-time risk scoring engine that evaluates:
  • Customer profile
  • Transaction context
  • Behavioral patterns
• Deliver sub-second decisioning to support transaction processing

• Design and implement pipelines for:
  • Event ingestion (transactions, customer actions, external signals)
  • Feature engineering (velocity metrics, behavioral aggregates)
• Maintain both real-time and historical data layers for monitoring and analytics

• Develop models for:
  • Anomaly detection
  • Behavioral profiling
  • Risk signal enhancement
• Focus on:
  • Explainability (feature importance, reason codes)
  • Reduction of false positives
• Integrate ML on top of rules, not as a replacement

• Integrate the monitoring engine with:
  • Core transaction systems
  • Wallet and ledger infrastructure
  • KYC and sanctions screening systems
  • External risk and data providers
• Ensure full data traceability and consistency across all components

• Build alert generation logic based on defined risk thresholds
• Structure outputs for compliance workflows, including:
  • Alert generation
  • Case investigation support
  • Regulatory reporting readiness (e.g., STR/SAR)

• Implement:
  • Rule performance monitoring
  • Model monitoring and drift detection
  • Alert quality tracking (false positives vs. true positives)
• Continuously improve detection accuracy and operational efficiency

• 3+ years experience in:
  • Backend engineering, data engineering, or machine learning
  • Experience in fintech, payments, fraud, or AML is strongly preferred
• Strong proficiency in:
  • Python
  • SQL
  • Working with transactional and time-series data
• Experience building:
  • Real-time or event-driven systems
  • Data pipelines and feature computation systems
• Understanding of:
  • AML/CFT concepts (sanctions, PEP, structuring, velocity monitoring, etc.)
  • Risk-based transaction monitoring frameworks
• Proven experience deploying systems in production environments

• Experience building fraud or AML monitoring systems
• Familiarity with:
  • Kafka or event streaming systems
  • Feature stores
  • Graph/network analysis (entity linking, money movement patterns)
• Experience working in regulated environments or supporting audits

• Strong systems thinker (not just model-focused)
• Ability to translate compliance requirements into scalable technical systems
• Attention to detail, especially around auditability and explainability
• Ability to build modular, production-grade infrastructure from scratch

You will be building a core piece of infrastructure that directly protects the platform, enables regulatory compliance, and supports long-term growth.

This system is being designed not only for internal use, but with the potential to evolve into a standalone product for other fintechs and partners.

• Relevant projects or systems you’ve built
• Experience with fraud, AML, or risk systems (if applicable)
• Links to GitHub or portfolio (if available)