Data Scientist (Fraud)

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.

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 .

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 voi ces 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 .

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.