About the Role
Moniepoint is a leading financial technology company digitising Africa’s real economy by building a comprehensive financial ecosystem for businesses. We are looking for a talented Data Scientist to sit at the heart of our fraud prevention operations. In this high-impact role, you will design the models, experiments, and detection systems that safeguard millions of customers and merchants across our platform, collaborating with cross-functional teams to tackle complex challenges in financial crime.
Key Responsibilities- Prototype, evaluate, and deploy machine learning models for fraud detection, maintaining ongoing monitoring and retraining cycles.
- Design and execute experiments to measure the impact of fraud interventions while balancing customer experience against loss reduction.
- Size fraud typologies across our diverse product lines to inform strategic prioritization and investment decisions.
- Build and maintain robust anomaly detection systems to surface novel fraud vectors before they scale.
- Partner closely with fraud operations, engineering, product management, and data analysts to translate technical insights into real-world mitigations.
- A strong foundation in statistics with a degree in a quantitative field such as Statistics, Mathematics, Engineering, or Computer Science.
- Minimum of 3 years of experience in data science, decision science, or risk analytics within fraud, payments, or financial services.
- Hands-on experience building, deploying, and monitoring machine learning models in a production environment.
- Proficiency in Python and SQL with strong expertise in the full model development lifecycle.
- Demonstrated ability to communicate complex technical findings clearly to non-technical stakeholders and drive actionable outcomes.
- Competitive salary with attractive compensation packages including pension and comprehensive health insurance.
- Annual performance bonus and additional employee benefits designed to support financial wellbeing.
- A people-first company culture that prioritizes team member wellness, inclusion, and open communication.
- Continuous learning environment featuring knowledge sharing, dedicated training, and regular technical talks.