Data Scientist (Fraud)

<p>&nbsp;</p> <p><strong>Who we are</strong></p> <p><span data-path-to-node=&quot;12,1&quot;><span class=&quot;citation-119&quot;>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</span></span><span data-path-to-node=&quot;12,3&quot;>.&nbsp;</span><span data-path-to-node=&quot;12,5&quot;><span class=&quot;citation-118&quot;>Our mission is to enable financial happiness for every African, everywhere</span></span><span data-path-to-node=&quot;12,7&quot;>.</span></p> <p data-path-to-node=&quot;6&quot;><strong data-path-to-node=&quot;6&quot; data-index-in-node=&quot;0&quot;>About this role:</strong></p> <p id=&quot;p-rc_0cd24779a7324afc-115&quot; data-path-to-node=&quot;7&quot;><span data-path-to-node=&quot;7,0&quot;>We&#39;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</span><span data-path-to-node=&quot;7,2&quot;>. 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</span><span data-path-to-node=&quot;7,4&quot;>.</span></p> <p id=&quot;p-rc_0cd24779a7324afc-116&quot; data-path-to-node=&quot;8&quot;><span data-path-to-node=&quot;8,0&quot;>You are a data-driven, intellectually curious Data Scientist who is energized by hard problems in fraud and financial crime</span><span data-path-to-node=&quot;8,2&quot;>. You&#39;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</span><span data-path-to-node=&quot;8,4&quot;>.</span></p> <p data-path-to-node=&quot;9&quot;><strong data-path-to-node=&quot;9&quot; data-index-in-node=&quot;0&quot;>Responsibilities:</strong></p> <ul data-path-to-node=&quot;10&quot;> <li> <p id=&quot;p-rc_0cd24779a7324afc-117&quot; data-path-to-node=&quot;10,0,0&quot;><span data-path-to-node=&quot;10,0,0,0&quot;>Prototype, evaluate, and help produce machine learning models for fraud detection; own their ongoing monitoring and retraining cycles</span><span data-path-to-node=&quot;10,0,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-118&quot; data-path-to-node=&quot;10,1,0&quot;><span data-path-to-node=&quot;10,1,0,0&quot;>Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction</span><span data-path-to-node=&quot;10,1,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-119&quot; data-path-to-node=&quot;10,2,0&quot;><span data-path-to-node=&quot;10,2,0,0&quot;>Size fraud typologies across our product lines to inform prioritization and investment decisions</span><span data-path-to-node=&quot;10,2,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-120&quot; data-path-to-node=&quot;10,3,0&quot;><span data-path-to-node=&quot;10,3,0,0&quot;>Build and maintain anomaly detection systems to surface novel fraud vectors before they scale</span><span data-path-to-node=&quot;10,3,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-121&quot; data-path-to-node=&quot;10,4,0&quot;><span data-path-to-node=&quot;10,4,0,0&quot;>Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations</span><span data-path-to-node=&quot;10,4,0,2&quot;>.</span></p> </li> </ul> <p data-path-to-node=&quot;11&quot;><strong data-path-to-node=&quot;11&quot; data-index-in-node=&quot;0&quot;>Experience &amp; Background:</strong></p> <ul data-path-to-node=&quot;12&quot;> <li> <p>A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar).</p> </li> <li> <p>3+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime.</p> </li> <li> <p>Hands-on experience building and deploying machine learning models in a production environment.</p> </li> <li> <p>Fraud, risk, or financial services experience is a strong plus.</p> </li> <li> <p>Solid grounding in data science fundamentals: experimentation, statistical inference, model evaluation, and feature engineering.</p> </li> <li> <p>Comfort working in fast-paced, cross-functional teams with high ownership expectations.</p> </li> </ul> <p data-path-to-node=&quot;13&quot;><strong data-path-to-node=&quot;13&quot; data-index-in-node=&quot;0&quot;>Skills &amp; Competencies:</strong></p> <ul data-path-to-node=&quot;14&quot;> <li> <p id=&quot;p-rc_0cd24779a7324afc-126&quot; data-path-to-node=&quot;14,0,0&quot;><span data-path-to-node=&quot;14,0,0,0&quot;>Proficiency in Python and SQL; comfort working across the full model development lifecycle</span><span data-path-to-node=&quot;14,0,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-127&quot; data-path-to-node=&quot;14,1,0&quot;><span data-path-to-node=&quot;14,1,0,0&quot;>An investigative instinct — you enjoy digging into data to find patterns others miss</span><span data-path-to-node=&quot;14,1,0,2&quot;>.</span></p> </li> <li> <p id=&quot;p-rc_0cd24779a7324afc-128&quot; data-path-to-node=&quot;14,2,0&quot;><span data-path-to-node=&quot;14,2,0,0&quot;>The ability to communicate technical findings clearly to non-technical stakeholders and translate insights into action</span><span data-path-to-node=&quot;14,2,0,2&quot;>.</span></p> </li> </ul> <p data-path-to-node=&quot;15&quot;><strong data-path-to-node=&quot;15&quot; data-index-in-node=&quot;0&quot;>What Success Looks Like in This Role:</strong></p> <ul data-path-to-node=&quot;16&quot;> <li> <p id=&quot;p-rc_0cd24779a732…