Data Scientist (Fraud)

Moniepoint; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health Insurance

Pension

Annual Bonus

Job summary

Moniepoint Inc. is hiring a Data Scientist to drive fraud detection across our platform. You will prototype and deploy ML models, design experiments, and surface novel fraud signals in collaboration with engineers, product managers, and analysts.

You’ll be part of a data-driven team focused on reducing fraud while maintaining customer experience, with hands-on model development and production readiness at the core of the role.

Qualifications

• Strong foundation in statistics, with a quantitative degree.
• 3+ years in data science, risk analytics, or fraud-related roles.
• Hands-on experience building and deploying ML models in production.
• Fraud, risk, or financial services experience is a plus.
• Fundamentals: experimentation, inference, evaluation, feature engineering.

Responsibilities

• Prototype and evaluate ML models for fraud detection; monitor and retrain.
• Design experiments to measure fraud interventions and balance UX with loss reduction.
• Characterize fraud typologies across product lines to guide prioritization.
• Build and maintain anomaly detection systems for early fraud signals.
• Collaborate with engineers, PMs, and analysts to operationalize model outputs.

Skills

Python

SQL

Fraud analytics

Education

Statistics degree

Job description

Who we are

Ranked in 2024 by the Financial Times, the company 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 this 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 the company detects and responds to emerging fraud threats.

You are a data-driven, intellectually curious Data Scientist who is energized 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.

Responsibilities:

• Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.
• Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.
• Size fraud typologies across our product lines to inform prioritization and investment decisions.
• Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.
• Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real‑world mitigations.

Experience & Background:

• A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
• 3+ 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.
• Comfort working in fast‑paced, cross‑functional teams with high ownership expectations.

Skills & Competencies:

• 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.

What Success Looks Like in This Role:

• Production‑grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale.
• Well‑designed experiments that successfully balance customer experience against fraud loss reduction.
• Clear sizing of fraud typologies that effectively drives product prioritization and strategic investment decisions.
• Seamless cross‑functional alignment where technical model outputs are consistently translated into real‑world fraud mitigations.

Why Join Us?

• 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, annual bonus, plus other benefits.

the company is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.