Data Scientist (Fraud)

Moniepoint; South Africa; On-site; ZAR 700,000 - 1,200,000; Full time

Job summary

Moniepoint in South Africa seeks a Data Scientist to join the fraud-fighting core. You’ll prototype and deploy ML models, run experiments, and uncover fraud signals across the ecosystem, partnering with engineers, product managers, and analysts to translate insights into production-grade systems.

The role emphasizes data-driven problem solving, model monitoring, and iterating experiments to balance customer experience with risk reduction.

Qualifications

• 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.
• 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 .

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 .

Skills

Python

SQL

Fraud detection

Machine Learning

Education

Bachelor's degree in Statistics/Mathematics/CS

Tools

TensorFlow

Scikit-learn

Job description

Ranked in 2024 by the Financial Times, Moniepoint is Africa’s fastest-growing fintech, trusted by over 10 million business and individual accounts, processing billions of Naira in transactions monthly . Our mission is to enable financial happiness for every African, everywhere .

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.

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 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.

Help Us Support Diversity at Moniepoint

At Moniepoint, we are committed to fostering a diverse and inclusive work environment. We do not discriminate based on gender identity, orientation, or other personal characteristics. To help us track and improve our recruitment efforts and ensure we are meeting our gender inclusion goals, we kindly ask you to answer the following demographic questions. Your responses are voluntary and will not impact your application in any way. Thank you for helping us build a more inclusive team