Senior Data Scientist (Fraud)

Who we are

Moniepoint is a global 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.

Our mission is simple: to enable financial happiness for every African, everywhere. And this is day one. 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.

We onboard over a million new customers each month, process hundreds of billions of dollars in payments annually, and support tens of millions of users across our ecosystem. Our India team is a core part of this scale, with ~100 teammates based across Bengaluru, Mumbai, Pune, Chennai, Hyderabad, and Gurgaon. You’ll work in a fast-paced, high-impact environment alongside experienced operators from companies such as Gojek, Tide, Amazon, Walmart, Paytm, BharatPe, Zeta, Delivery Hero, Grab, and Groupon. If you want to build at scale, work with one of Africa’s highest-volume fintech data sets, and ship products that materially impact tens of millions of users, this is an exceptional time to join.

About the role

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.

You’ll partner closely with Fraud, Risk, Product, and Engineering teams to design, build, and deploy production fraud models that sit directly in decision flows. 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.

What You’ll Do

• Develop and deploy fraud detection, transaction monitoring, and behavioural risk models across payments, accounts, onboarding, and merchant activity
• Design and run experiments to optimise fraud catch rates, false positives, and customer friction
• Partner with product and engineering teams to embed models into real-time decisioning systems
• 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
• Support investigations, strategy, and policy teams with advanced fraud analytics
• Mentor analysts and product teams on experimentation, detection strategy, and data-driven decision making

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 with fraud detection, transaction monitoring, or behavioural risk modelling
• Proficiency in SQL and at least one modelling/programming language (Python or R)