Data Scientist (Fraud)

Job title : Data Scientist (Fraud)

Job Location : Lagos Deadline : October 11, 2026 Quick Recommended Links

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About this role

• We're looking for a Data Scientist to sit at the heart of how we fight fraud — building the models, experiments, and detection systems that protect millions of customers and merchants across our platform.
• This is a high-impact role at the intersection of machine learning, product, and engineering, where your work will directly shape how Moniepoint detects and responds to emerging fraud threats.
• You are a data-driven, intellectually curious Data Scientist who is energized by hard problems in fraud and financial crime.
• You'll prototype and ship ML models, design experiments, and uncover new fraud signals across our ecosystem — partnering closely with engineers, product managers, and analysts to turn your work into production-grade systems.

Responsibilities

• Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.
• Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.
• Size fraud typologies across our product lines to inform prioritization and investment decisions.
• Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.
• Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.

Experience & Background

• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
• 3+ 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.
• Comfort working in fast-paced, cross-functional teams with high ownership expectations.

Skills & Competencies:

• 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.

What Success Looks Like in This Role:

• Production-grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale.
• Well-designed experiments that successfully balance customer experience against fraud loss reduction.
• Clear sizing of fraud typologies that effectively drives product prioritization and strategic investment decisions.
• Seamless cross-functional alignment where technical model outputs are consistently translated into real-world fraud mitigations.

Why Join Us?

• Culture: We put our people first and prioritize 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, annual bonus, plus other benefits.