Senior Data Scientist (Fraud)

Moniepoint Group; Greater London; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

Health insurance

Monthly bonuses

Learning and development opportunities

Job summary

Moniepoint Group, located in Greater London, is seeking a skilled Data Scientist to focus on fraud detection. This critical position involves building models and systems that protect millions across our platform. The ideal candidate will have over 5 years in data science, with a strong foundation in statistics and machine learning.

The role offers a supportive culture, opportunities for learning, and an attractive salary package including health insurance and bonuses.

Qualifications

• 5+ years of experience in data science or risk analytics within fraud.
• Solid grounding in data science fundamentals.
• Comfort working in fast-paced, cross-functional teams.

Responsibilities

• Prototype and evaluate machine learning models for fraud detection.
• Design experiments to measure the impact of fraud interventions.
• Build and maintain anomaly detection systems.

Skills

Statistics

Machine learning

Python

SQL

Fraud detection

Data analysis

Education

Degree in a quantitative field

Tools

Machine learning frameworks

Data visualization tools

Job description

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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.

• 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.