
1001 - 5000 employees
💳 Fintech
🏦 Banking
Fintech • Banking • Payments
Moniepoint Inc. is Africa's all-in-one financial ecosystem that provides seamless solutions in payments, banking, credit, and business management for over 10 million businesses and individuals. Operating as Nigeria's largest merchant acquirer, Moniepoint powers the majority of Point of Sale (POS) transactions in the country. The company processes $17 billion monthly while ensuring profitable operations. With operations starting in 2019, Moniepoint continues to support businesses through its comprehensive financial services platform, making significant strides in financial inclusion across emerging markets.
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1001 - 5000 employees
💳 Fintech
🏦 Banking
Fintech • Banking • Payments
Moniepoint Inc. is Africa's all-in-one financial ecosystem that provides seamless solutions in payments, banking, credit, and business management for over 10 million businesses and individuals. Operating as Nigeria's largest merchant acquirer, Moniepoint powers the majority of Point of Sale (POS) transactions in the country. The company processes $17 billion monthly while ensuring profitable operations. With operations starting in 2019, Moniepoint continues to support businesses through its comprehensive financial services platform, making significant strides in financial inclusion across emerging markets.
• Model Development: Prototype, evaluate, and help productionize machine learning models for fraud detection; own their ongoing monitoring and retraining cycles. • Experimentation: Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction. • Risk Assessment: Size fraud typologies across our product lines to inform prioritisation and investment decisions. • System Maintenance: Build and maintain anomaly detection systems to surface novel fraud vectors before they scale. • Cross-Functional Collaboration: Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.
• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar) • 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime • Hands-on experience building and deploying machine learning models in a production environment, fraud, risk, or financial services experience is a strong plus • Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering • Proficiency in Python and SQL; comfort working across the full model development lifecycle • An investigative instinct, you enjoy digging into data to find patterns others miss • The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action • Comfort working in fast-paced, cross-functional teams with high ownership expectations
• Culture: We put our people first and prioritise the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human. • Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. • Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits
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