Technical Financial Crime Manager (Fintech/Payments/African Experience)
Skills
About This Role
Technical Financial Crime Manager (Fintech/Payments/African Experience)
Our client is a technology company solving payments problems for businesses.
Their mission is to help businesses in Africa become profitable, envied, and loved.
They provide a suite of products to help businesses accept payments online and offline, manage their operations, and grow their business.
Our client is driven by a commitment to excellence, innovation, and customer satisfaction.
Role Overview
- 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 our client 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
- Translating risk, regulatory, and business requirements into scalable detection systems
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 in Africa required.
Preferred
- Experience with dbt and modern analytics stacks.
- Experience with version control systems (GitHub).
- Experience with AI-assisted tooling or advanced analytics platforms.
- Familiarity with monitoring platforms, alerting systems, transaction screening, and case management tools.
- Experience working with OLTP (MySQL/PostgreSQL/SQL Server), OLAP (Redshift/BigQuery/Snowflake), and NoSQL (MongoDB) databases.
- Industry certifications such as ACAMS, ICA, CFE, CFCS, or similar.
Technical Ownership of Detection & Monitoring
- Define, build, test, and optimise fraud and AML detection rules, scenarios, thresholds, and models used in production systems.
- Translate complex datasets and domain insights into actionable detection logic embedded in monitoring and alerting platforms.
- Establish feedback loops between investigation outcomes and detection logic to continuously improve signal quality.
- Measure and manage detection performance using quantitative metrics (precision, recall, false positives, alert-to-case conversion, loss metrics).
- 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.
- 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.
- 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.
- Apply deep understanding of fraud typologies, AML/CTF risks, sanctions, and regulatory expectations to detection design.
- Manage the Fraud and AML operational teams (specialists and first-line managers) to ensure adequate coverage, capability and day-to-day execution.
- Translate regulatory, partner, and audit requirements into scalable technical and operational controls.
- Stay ahead of evolving financial crime patterns, market-specific risks, and regulatory developments across our client’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.
- Drive automation initiatives to reduce manual effort, improve consistency, and enable scale without compromising control quality.
- Identify and prioritise enhancements to monitoring platforms, workflows, and data pipelines.
- 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.
- Use data and metrics to manage performance, capacity, and outcomes, ensuring teams operate efficiently and effectively.
- Identify gaps, risks, and inefficiencies, leading initiatives to strengthen controls and scale operations sustainably.
- 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.
- Influence roadmap priorities related to fraud, AML, and financial crime tooling.
- Provide clear updates to senior stakeholders on operational performance, risks, and emerging issues
- Support audits, partner reviews, and regulatory engagements as a subject matter expert.
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