Data Scientist - Fraud Detection

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.