Data Scientist (Fraud)

Remote办公方式未标注

全职Data & analytics

薪资未披露

签证支持雇主未明示 · 无官方资质名单可查

🛡 岗位真实性核验

Ghost Job 检测

⏳ 岗位入库已 0 天

🛡 申请链接 2026-10-31 核验有效

📈 该公司近 30 天发布 1 个岗位——招聘节奏正常

信号由后台自动核验生成，仅供参考；判断权在你。设计案：GHOST-JOB-P1

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必备技能

AnalyticsAnomaly DetectionData ScienceFeature EngineeringFintechModel EvaluationNode.jsPythonSQLStatistics

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

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职位描述

Who we are
Ranked in 2024 by the Financial Times, Moniepoint 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 Moniepoint 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:
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Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles.
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Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction.
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Size fraud typologies across our product lines to inform prioritization and investment decisions.
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Build and maintain anomaly detection systems to surface novel fraud vectors before they scale.
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Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.
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Experience & Background:
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A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).
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3+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime.
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Hands-on experience building and deploying machine learning models in a production environment.
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Fraud, risk, or financial services experience is a strong plus.
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Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering.
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Comfort working in fast-paced, cross-functional teams with high ownership expectations.
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Skills & Competencies:
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Proficiency in Python and SQL; comfort working across the full model development lifecycle.
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An investigative instinct — you enjoy digging into data to find patterns others miss.
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The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action.
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What Success Looks Like in This Role:
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Production-grade ML models and anomaly detection systems that effectively surface and mitigate novel fraud vectors before they scale.
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Well-designed experiments that successfully balance customer experience against fraud loss reduction.
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Clear sizing of fraud typologies that effectively drives product prioritization and strategic investment decisions.
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Seamless cross-functional alignment where technical model outputs are consistently translated into real-world fraud mitigations.
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Why Join Us?
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<li data-path-to-node="17">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.</li>
<li data-path-to-node="17">Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.</li>
<li data-path-to-node="17">Compensation: You'll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.</li>
</ul>
Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates. Find more English Speaking Jobs in United Kingdom on Arbeitnow

🈯 翻译这份 JD · 红灯 0 / 黄灯 1 / 绿灯 1点开 ▾

可以投——没有红灯，黄灯问题放进面试清单问清即可。另有 1 条主动欢迎信号——加分。

🤝 we celebrate diversity → EEO 声明明文（常规但正面）

fast-paced → 流程不成熟、需求常变要问的问题：「节奏快」的交付周期是多久？需求由谁定？

plus → 加分项，不是门槛

词典只标"常见信号"，不对公司下结论——红灯 = 面试里该当面确认的问题。想自己翻别的 JD：JD 翻译器 →

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公司 · Company

Moniepoint

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Remote来源：公开招聘平台

⚑ 岗位信息收录自公开招聘页（公开招聘平台），以雇主官网为准