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Senior Data Scientist (Fraud)

External
moniepoint logoMoniepoint · Remote
Full-timeRemote1w ago
Core DataLinearMachine LearningPythonSQL
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About the role

Moniepoint Inc. is Africa's all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month. As Nigeria's largest merchant acquirer, we power most of the country's point-of-sale (POS) transactions. Through our subsidiaries, Moniepoint Inc. processes over $250 billion in digital payment transaction value annually. 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. Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

Responsibilities

  • 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)
  • Experience with machine learning, anomaly detection, network/graph features, and real-time decision systems
  • Strong intuition for fraud typologies, adversarial behaviour, and evolving attack patterns
  • Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical stakeholders
  • High ownership mindset and comfort working in fast-paced, cross-functional product environments
  • What we can offer you
  • Culture: We put our people first and prioritize 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
  • A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms).
  • A take-home assignment
  • A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
  • A behavioural and technical interview with the hiring manager
  • Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Benefits

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