Work Link Nigeria

Company: Paystack

Location: Lagos, Nigeria

Industry: Fintech

Job Type: Full-time

🌍 Overview

Paystack is a pioneer in African fintech with a mission to help merchants get paid by anyone, anywhere in the world, processing over $300 million in monthly transactions. The Technical Financial Crime Manager role owns, designs, and scales fraud and AML detection capabilities. This hands-on technical leadership position sits at the intersection of data, engineering, and financial crime operations with end-to-end accountability for technically robust, domain-accurate, and scalable monitoring systems across multiple markets. You will run the day-to-day fraud and AML detection stack, combine deep technical expertise with financial crime domain knowledge, manage domain specialists, and ensure Paystack remains a safe, trusted payments platform.

⚙️ Key Responsibilities

• Technical Ownership of Detection & Monitoring: Define, build, test, and optimise fraud and AML detection rules, scenarios, thresholds, and models used in production systems.
• Technical Ownership of Detection & Monitoring: Translate complex datasets and domain insights into actionable detection logic embedded in monitoring and alerting platforms.
• Technical Ownership of Detection & Monitoring: Establish feedback loops between investigation outcomes and detection logic to continuously improve signal quality.
• Technical Ownership of Detection & Monitoring: Measure and manage detection performance using quantitative metrics (precision, recall, false positives, alert-to-case conversion, loss metrics).
• Technical Ownership of Detection & Monitoring: Maintain structured, auditable documentation of rules, logic, assumptions, and changes.
• Data Analysis, Modelling & Insights: Analyse large, complex transactional and behavioural datasets to identify emerging fraud and AML risks across markets.
• Data Analysis, Modelling & Insights: Design and implement statistical models, machine learning approaches, and/or time-series analysis to enhance detection capabilities.
• Data Analysis, Modelling & Insights: Build and own dashboards and reporting frameworks tracking KPIs, SLAs, alert quality, investigator productivity, and risk outcomes.
• Data Analysis, Modelling & Insights: Conduct trend analysis, root cause analysis, and deep dives on losses, typologies, and control gaps.
• Financial Crime Oversight: Own the end-to-end fraud and AML detection domain, ensuring alignment between prevention, detection, investigation, and remediation.
• Financial Crime Oversight: Apply deep understanding of fraud typologies, AML/CTF risks, sanctions, and regulatory expectations to detection design.
• Financial Crime Oversight: Manage the Fraud and AML operational teams (specialists and first-line managers) to ensure adequate coverage, capability and day-to-day execution.
• Financial Crime Oversight: Translate regulatory, partner, and audit requirements into scalable technical and operational controls.
• Financial Crime Oversight: Stay ahead of evolving financial crime patterns, market-specific risks, and regulatory developments across Paystack’s footprint.
• Tooling, Automation & Scale: Partner with Product and Engineering to embed detection logic into core systems and improve monitoring, alerting, and case management tooling.
• Tooling, Automation & Scale: Drive automation initiatives to reduce manual effort, improve consistency, and enable scale without compromising control quality.
• Tooling, Automation & Scale: Identify and prioritise enhancements to monitoring platforms, workflows, and data pipelines.
• Tooling, Automation & Scale: Ensure fraud and AML tooling evolves in line with transaction growth, new products, and new markets.
• Operational Excellence: Build and continuously improve operational processes, SLAs, KPIs, and quality frameworks across Fraud and AML teams.
• Operational Excellence: Use data and metrics to manage performance, capacity, and outcomes, ensuring teams operate efficiently and effectively.
• Operational Excellence: Identify gaps, risks, and inefficiencies, leading initiatives to strengthen controls and scale operations sustainably.
• Operational Excellence: Balance speed, quality, regulatory expectations, and customer experience in day-to-day decision-making.
• Cross-Functional & Executive Collaboration: Work closely with Product, Engineering, Data, Risk, Compliance, Legal, and Customer Operations.
• Cross-Functional & Executive Collaboration: Influence roadmap priorities related to fraud, AML, and financial crime tooling.
• Cross-Functional & Executive Collaboration: Provide clear updates to senior stakeholders on operational performance, risks, and emerging issues.
• Cross-Functional & Executive Collaboration: Support audits, partner reviews, and regulatory engagements as a subject matter expert.

🎓 Requirements

• 7+ years in financial crime roles in payments, fintech, banking, or financial services
• Strong technical expertise in data analysis, including advanced SQL and experience working with large, complex datasets
• Expert Python skills, including experience with libraries such as pandas, NumPy, scikit-learn, statsmodels, and/or model pipelines
• Proven experience designing, building, and tuning risk detection systems (fraud, AML, or similar)
• Solid understanding of statistical modelling, machine learning, and/or time-series forecasting, with experience deploying models into production or operational workflows
• Ability to translate data insights into operational detection logic used by investigators and automated systems
• Experience measuring and optimising detection performance using quantitative metrics
• Strong systems thinking: able to design scalable, maintainable monitoring frameworks rather than one-off rules
• Deep understanding of financial crime typologies, fraud patterns, AML/CTF requirements, and regulatory obligations
• Experience operating within fraud, AML, risk, or compliance functions in payments, fintech, or financial services
• Proven experience leading and developing teams, including setting direction, coaching, and performance management
• Ability to balance technical depth with practical operational decision-making
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders
• High ownership mindset and comfort operating in ambiguous, high-growth environments
• Experience with dbt and modern analytics stacks (Preferred)
• Experience with version control systems (GitHub) (Preferred)
• Experience with AI-assisted tooling or advanced analytics platforms (Preferred)
• Familiarity with monitoring platforms, alerting systems, transaction screening, and case management tools (Preferred)
• Experience working with OLTP (MySQL/PostgreSQL/SQL Server), OLAP (Redshift/BigQuery/Snowflake), and NoSQL (MongoDB) databases (Preferred)
• Industry certifications such as ACAMS, ICA, CFE, CFCS, or similar (Preferred)

💼 Work Structure & Compensation

• Salary: (Not stated)
• Work Mode: On-site

🧾 How to Apply

Interested candidates should APPLY HERE

Application Deadline: Ongoing

Source: Greenhouse (Paystack Careers)

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