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Technical Financial Crime Manager
Paystack
Posted 3 months agoLagos, Nigeria
Location
Lagos, Nigeria
Job Type
Full-time
Experience
Senior
Category
Banking & Finance
Job Description
Technical
Financial
Crime
Manager
About
Paystack
Over the past nine years,
Paystack has established itself as 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, our modern payments infrastructure supports tens of thousands of notable corporations, including MTN,
Bolt, and
Domino’s
Pizza.
As we enter a phase of accelerated growth, we are seeking a
Technical
Financial
Crime
Manager to own, design, and scale our fraud and AML detection capabilities.
This role sits at the intersection of data, engineering, and financial crime operations, with end-to-end accountability for ensuring our monitoring systems are technically robust, domain-accurate, and scalable across multiple markets.
This is a hands-on technical leadership role.
You will define detection logic, guide system design, and directly influence how financial crime risk is identified and managed at
Paystack, while also leading and developing high-performing fraud and AML teams.
What You’ll Do As the Technical Financial Crime Manager, you will run the day-to-day fraud and AML detection stack; from data and rules to operational outcomes.
You will combine deep technical expertise with financial crime domain knowledge to design effective monitoring systems, manage domain specialists, and ensure Paystack remains a safe, trusted payments platform.
You will be accountable for: The technical quality and effectiveness of fraud & AML monitoring logic The operating model and performance of Financial Crime Monitoring teams 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.
Data Analysis, Modelling & Insights Analyse large, complex transactional and behavioural datasets to identify emerging fraud and AML risks across markets.
Financial Crime Ove
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Requirements
- 7+ years in financial crime roles in payments, fintech, banking, or financial services.
- Expert Python skills including pandas, NumPy, scikit-learn, statsmodels, and model pipelines.
- Proven experience designing, building, and tuning risk detection systems (fraud, AML, or similar)
- Deep understanding of financial crime typologies, fraud patterns, AML/CTF requirements, and regulatory obligations.
- Proven experience leading and developing teams, including setting direction, coaching, and performance management.
- This role is open to candidates based in Nigeria, Ghana, Kenya, or South Africa.
Responsibilities
- Establish feedback loops between investigation outcomes and detection logic to continuously improve signal quality.
- Maintain structured, auditable documentation of rules, logic, assumptions, and changes.
- Conduct trend analysis, root cause analysis, and deep dives on losses, typologies, and control gaps.
- Apply deep understanding of fraud typologies, AML/CTF risks, sanctions, and regulatory expectations to det.
- Translate complex datasets and domain insights into actionable detection logic embedded in monitoring and alerting platforms.
- Measure and manage detection performance using quantitative metrics (precision, recall, false positives, alert-to-case conversion, loss metrics)
- Design and implement statistical models, machine learning approaches, and/or time-series analysis to enhance detection capabilities.
- Build and own dashboards and reporting frameworks tracking KPIs, SLAs, alert quality, investigator productivity, and risk outcomes.
Benefits
- Competitive compensation and benefits package.
- High-impact role defining financial crime detection at one of Africa's leading fintech companies.
- Opportunity to work across multiple African markets.
How to Apply
Apply via Paystack's Greenhouse job board.