Moniepoint is a general fintech building modern financial services for millions of people and businesses across high-growth markets. We provide payments, banking, credit, and financial management tools - reliable products that people and businesses use every day to run their lives, grow their companies, and move money safely.
We've grown rapidly in Nigeria and the UK, and we're now expanding our product, engineering, and analytics teams. Our work ranges from building financial infrastructure to designing intuitive customer experiences for emerging markets - solving real, meaningful problems at scale.
If you want to build our data science function from the ground up, work with one of Africa's highest-scale fintech data sets, and ship products that influence tens of millions of users, this is an exceptional time to join.
We're looking for a hands-on Senior Data Scientist (Fraud) to help detect, prevent, and reduce fraud across one of the largest financial transaction ecosystems in Africa. Operating at the heart of real-time payments, identity, behavioural risk, and transaction monitoring, this role works at massive scale with direct, real-world impact.
Sitting at the intersection of data science, fraud strategy, and product, you'll translate complex behavioural signals into high-confidence, real-time decisions - balancing fraud loss, customer experience, and regulatory expectations to protect millions of customers and businesses.
Develop and deploy fraud detection, transaction monitoring, and behavioural risk models across payments, accounts, onboarding, and merchant activity




Build features from high-volume transactional, device, network, and behavioural data
Continuously monitor model performance, drift, and emerging fraud patterns
Ensure data quality, governance, and responsible use of models in regulated environments
Mentor analysts and product teams on experimentation, detection strategy, and data-driven decision making
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 with fraud detection, transaction monitoring, or behavioural risk modelling
Proficiency in SQL and at least one modelling/programming language (Python or R)
Experience with machine learning, anomaly detection, network/graph features, and real-time decision systems
Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical stakeholders
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
A coding exercise on HackerRank – covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth

📌 Data Scientist Senior - Machine Learning (Málaga)
🏢 Moniepoint
📍 Málaga