Data Scientist – Fraud Detection

About the role

Moniepoint is looking for a Data Scientist to strengthen its fraud‑fighting capabilities. You will work closely with engineering, product and fraud operations to design, build and maintain machine‑learning models that protect customers and merchants from abusive transactions.

Key responsibilities

• Develop, evaluate and deploy machine‑learning models for fraud detection, monitoring their performance in production and iterating as needed.
• Design controlled experiments to measure the impact of fraud interventions, balancing customer friction with loss reduction.
• Quantify fraud typologies across product lines and produce insights that guide investment decisions.
• Build anomaly‑detection tools and heuristics to flag emerging fraud patterns early.
• Collaborate with software engineers, product managers and analysts to translate model outputs into actionable mitigation workflows.
• Investigate unusual data patterns, propose new features or model improvements, and communicate findings to non‑technical stakeholders.

Required profile

• Strong statistical foundation with a degree in statistics, mathematics, engineering, computer science or a related quantitative discipline.
• Experience working with large transaction datasets and building production‑grade models.
• Ability to design experiments and interpret results in a business context.
• Excellent communication skills to convey technical trade‑offs to diverse audiences.

Required skills

• Machine learning
• Statistical analysis
• Anomaly detection

What we offer

• Competitive benefits package.
• Opportunity to work on high‑impact problems in a fast‑growing fintech environment.