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Quick apply
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Senior Data Scientist (Fraud)

Moniepoint -
Remote

Quick apply

Job details

3 hours ago

Benefits

Company pension

Qualifications

SQL
Machine learning
Financial services
Data science
Python

Full job description

Who we are

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 the 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. We are looking for a data-driven, intellectually curious Data Scientist who is energised 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.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What You'll Do

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

We would love to hear from you if…

A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar)
5+ 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
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
Comfort working in fast-paced, cross-functional teams with high ownership expectations

What we can offer you

Culture: We put our people first and prioritise 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, monthly bonuses, plus other benefits

What to expect in the hiring process

A preliminary phone call with the recruiter
An interview with a business lead
Technical take-home task (SQL/Python test and case study)
A behavioural and technical interview with the Head of Data Science and a member of the executive team

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

Quick apply

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