Data Scientist, Fraud

🕒 July 29

🇵🇱 Poland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Moniepoint Inc. (Formerly TeamApt Inc.)

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💳 Fintech

🏦 Banking

Fintech • Banking • Payments

Moniepoint Inc. is Africa's all-in-one financial ecosystem that provides seamless solutions in payments, banking, credit, and business management for over 10 million businesses and individuals. Operating as Nigeria's largest merchant acquirer, Moniepoint powers the majority of Point of Sale (POS) transactions in the country. The company processes $17 billion monthly while ensuring profitable operations. With operations starting in 2019, Moniepoint continues to support businesses through its comprehensive financial services platform, making significant strides in financial inclusion across emerging markets.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• You'll receive an attractive salary • Pension • Health insurance • Annual bonus plus other benefits