Financial Crime Systems Engineer

Safaricom PLC is a telecommunications company founded in 1997 and based in Nairobi, Kenya.

The role is responsible for ensuring these systems operate effectively, leverage high-quality data, and deliver timely, risk-based insights to support the detection, prevention, and reporting of financial crime in line with regulatory requirements and Safaricom policies. The role works closely with Technology, Data Science and product teams with the analyst supporting system configuration, data integrity monitoring, alert analysis, and performance optimization. The role contributes to the implementation and adoption of intelligent financial crime solutions, leveraging automation, advanced analytics, artificial intelligence (AI), machine learning, and behavioural monitoring techniques to strengthen detection capabilities, improve alert quality, reduce false positives, and enhance operational efficiency across financial crime processes. The Financial Crime Systems Engineer also plays a key role in supporting digital transformation and innovation initiatives by identifying opportunities to automate manual activities, streamline investigations, enhance management reporting, and improve decision-making through data-driven insights. The role supports regulatory reviews, audits, model validations, and system enhancement projects while ensuring Safaricom maintains a resilient, scalable, and future-ready financial crime control environment capable of responding to evolving financial crime threats, emerging technologies, and changing regulatory expectations.

1. Support the administration, configuration, maintenance, and optimization of financial crime systems, including AML, Transaction Monitoring, Sanctions Screening, Customer Risk Rating, Fraud Detection, and Case Management platforms.
2. Ensure systems operate effectively, efficiently, and in line with regulatory requirements, industry standards, and internal policies.
3. Monitor system performance and recommend improvements to enhance effectiveness and operational resilience.
4. Monitor and validate data feeds, interfaces, and system inputs to ensure completeness, accuracy, timeliness, and integrity of financial crime data.
5. Investigate and resolve data quality issues impacting financial crime detection and reporting.
6. Collaborate with Data, Technology and Cyber teams to strengthen governance, controls, and data management practices for AML systems.
7. Support the tuning, calibration, and optimization of detection scenarios, rules, thresholds, and risk indicators.
8. Perform trend analysis on alerts, cases, and suspicious activity to identify opportunities for improving detection effectiveness.
9. Reduce false positives while maintaining regulatory compliance and enhancing risk detection capabilities.
10. Support the implementation and adoption of advanced analytics, artificial intelligence (AI), machine learning, and behavioural monitoring solutions.
11. Identify opportunities to automate manual processes and improve investigation workflows.
12. Contribute to initiatives that improve alert prioritization, risk scoring, and operational efficiency.
13. Assist with model validations, effectiveness assessments, and control testing exercises.
14. Participate in system upgrades, implementations, enhancements, testing, and change management activities.
15. Assist in gathering business requirements and translating financial crime risk management needs into system solutions.
16. Ensure enhancements are documented, tested, and implemented in accordance with governance standards.
17. Provide analytical and technical support to Financial Crime Compliance and Operations teams in the investigation of alerts and cases.
18. Develop and maintain system-generated reports, dashboards, and management information to support investigations and decision-making.
19. Support the escalation and reporting of significant system-related issues affecting financial crime controls.
20. Support regulatory reviews, audits, inspections, and independent assurance activities.
21. Develop and maintain meaningful management reports, dashboards, and key risk indicators (KRIs).
22. Produce analysis and insights on system performance, alert trends, detection effectiveness, and emerging risks.
23. Support senior management decision-making through accurate and timely reporting.
24. Work closely with all teams Sanctions, KYC, Investigations, Compliance, Operations, Data, Technology, Risk, and Business teams to enhance financial crime controls within Agile delivery.
25. Provide subject matter expertise on financial crime systems and technologies.
26. Facilitate effective communication between business and technical stakeholders during projects and system changes.
27. Identify opportunities to enhance financial crime detection capabilities through emerging technologies and industry best practices.
28. Support digital transformation initiatives aimed at improving efficiency, effectiveness, and customer outcomes.
29. Continuously review processes and controls to ensure the institution maintains a scalable, resilient, and future-ready financial crime framework.
30. Identify, assess, and escalate system-related financial crime risks and control weaknesses.
31. Ensure appropriate controls are implemented to mitigate risks associated with system failures, data integrity issues, and model performance.
32. Support ongoing monitoring of emerging financial crime typologies, threats, and regulatory developments.
33. Uphold the company code of conduct, policies and procedures, ensuring integrity and accountability in every aspect of your work.
34. All employees have a responsibility to adhere to safety, health and wellbeing policies, guidelines and procedures in all actions and decisions.

1. Relevant degree in Business, Engineering or IT Undergraduate Degree or relevant field along with professional qualifications.
2. Competencies in software development/system configuration data extraction technologies and platforms e.g. C#, Java, JavaScript, React.
3. Understanding of Agile Methodology, Machine learning, Bot development, Penetration Testing, QA, Project Management, Micro services, SANs security compliance, and Technical documentation.
4. At least 2 years as a software engineer/developer or data science experience.
5. Proficiency in data analysis and trend profiling using Power BI, Qlik Sense.