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About Moniepoint

Recognized by the Financial Times in 2024 as Africa's fastest-growing fintech, Moniepoint serves over 10 million business and individual accounts and processes billions of Naira in transactions each month. The company's dedication centers on delivering financial happiness to every African, wherever they are.

Role Overview

We are seeking a Data Scientist specializing in fraud detection to lead the development of machine learning models, experimental analyses, and detection systems that safeguard millions of users and merchants across our platform. This pivotal position connects machine learning, product strategy, and engineering efforts to enhance how emerging fraud threats are identified and handled.

Key Responsibilities

Develop, assess, and support machine learning models tailored to detect fraud, including managing their continuous monitoring and retraining processes.
Design and execute experiments to evaluate fraud intervention effectiveness, carefully weighing customer experience against reducing losses.
Analyze and quantify various fraud patterns across product lines to guide investment and prioritization decisions.
Create and sustain anomaly detection tools to identify new fraud methods before they escalate.
Collaborate closely with fraud operations, engineering, product management, and data analysis teams to transform model insights into practical fraud prevention measures.

Experience & Qualifications

Strong grounding in statistics complemented by a degree in a quantitative discipline such as Statistics, Mathematics, Engineering, or Computer Science.
At least three years of professional experience in data science, decision science, or risk analytics focusing on fraud, payments, or financial crime.
Demonstrated ability to build and deploy machine learning models in live production settings.
Experience in fraud, risk management, or financial services is highly advantageous.
Comprehensive understanding of data science principles including experimentation, statistical inference, model validation, and feature extraction.
Ability to thrive in dynamic, interdisciplinary teams with an emphasis on accountability.

Skills & Competencies

Expertise in Python programming and SQL with familiarity covering all stages of model development.
An analytical mindset that enjoys exploring data for subtle patterns often overlooked by others.
Clear communication skills enabling the translation of complex technical findings for non-specialist stakeholders and driving actionable outcomes.

Success Indicators

Implementation of production-level machine learning models and anomaly detection systems that identify and mitigate emerging fraud tactics early.
Well-executed experimental designs that effectively balance fraud loss reductions with positive customer experiences.
Accurate fraud typology assessments that inform strategic product decisions and budget allocations.
Effective collaboration ensuring that technical model outputs are applied as real-world fraud countermeasures.

Why Join Moniepoint?

People-Centric Culture: We prioritize our employees’ well-being, fostering an inclusive environment where everyone’s opinions are valued and respected.
Continuous Learning: The workplace encourages knowledge exchange, regular training sessions, and internal technical presentations.
Competitive Compensation: Employees receive a generous salary package, pension, health insurance, annual bonuses, and additional benefits.

Diversity & Inclusion

Moniepoint is committed to equal opportunity employment, welcoming diversity and cultivating an inclusive atmosphere for all team members and applicants.

Data Scientist - Fraud Detection