Opportunity at
MoniepointData Scientist (Fraud)
Moniepoint is recognized as Africa's fastest-growing fintech, supporting over 10 million personal and business accounts while processing billions of Naira in monthly transactions. The organization aims…
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About This Role
Moniepoint is recognized as Africa's fastest-growing fintech, supporting over 10 million personal and business accounts while processing billions of Naira in monthly transactions. The organization aims to deliver financial happiness throughout Africa. The company seeks a Data Scientist to join its fraud prevention team. In this position, the professional will develop models, experiments, and detection mechanisms to safeguard millions of users and merchants. Operating at the intersection of product, engineering,…
Job Description
Moniepoint is recognized as Africa's fastest-growing fintech, supporting over 10 million personal and business accounts while processing billions of Naira in monthly transactions. The organization aims to deliver financial happiness throughout Africa.
The company seeks a Data Scientist to join its fraud prevention team. In this position, the professional will develop models, experiments, and detection mechanisms to safeguard millions of users and merchants. Operating at the intersection of product, engineering, and machine learning, this role directly influences how the organization identifies and addresses emerging financial crime risks. The ideal candidate is intellectually curious, relies on data-driven approaches, and thrives on solving complex challenges in financial security.
Key duties involve building and evaluating machine learning algorithms for fraud detection, maintaining monitoring and retraining cycles, conducting experiments to assess interventions, and sizing fraud typologies to guide investments. Professionals will also construct anomaly detection systems to catch new threats early, collaborating closely with engineers, product managers, data analysts, and fraud operations teams.
Moniepoint fosters a human-centric culture that prioritizes employee well-being, respects diverse opinions, and encourages open communication. The organization also emphasizes continuous learning through knowledge sharing, training programs, and internal technical discussions, offering competitive compensation, health insurance, pension contributions, and annual bonuses.
Responsibilities
- Prototype, evaluate, and produce machine learning models dedicated to fraud detection
- Manage ongoing monitoring and retraining cycles for deployed models
- Design and execute experiments to measure the effectiveness of fraud interventions
- Balance customer experience outcomes against fraud loss reduction goals
- Size fraud typologies across product lines to direct prioritization and investment choices
- Build and maintain anomaly detection systems to uncover novel fraud vectors early
- Partner with fraud operations, engineering, product management, and data analysis teams to turn model outputs into real-world mitigations
Requirements
- Degree in a quantitative discipline such as Statistics, Mathematics, Engineering, or Computer Science
- Minimum of 3 years of professional experience in data science, decision science, or risk analytics within financial crime, payments, or fraud
- Demonstrated hands-on experience in building and deploying machine learning models into production
- Strong foundation in data science principles including feature engineering, experimentation, statistical inference, and model evaluation
- Proficiency in Python and SQL with capability across the full model development lifecycle
Qualifications
- Prior background working in fraud, risk, or financial services environments
Core Skills
Benefits
- Attractive salary
- Pension
- Health insurance
- Annual bonus
- Additional benefits
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location or remote policy for this role?
The source posting does not specify a location or state whether the role is remote, hybrid, or on-site.
What technical skills are required for the Data Scientist position?
Candidates must be proficient in Python and SQL, have hands-on experience building and deploying machine learning models in production, and possess a strong background in data science fundamentals like experimentation and feature engineering.
What level of experience is needed to apply?
Applicants need at least 3 years of experience in data science, decision science, or risk analytics specifically within fraud, financial crime, or payments.
What benefits are provided by Moniepoint?
Employees receive an attractive salary, a pension, health insurance, an annual bonus, and other benefits, along with access to training and knowledge-sharing initiatives.
Sample Interview Questions
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