Data Scientist - Fraud Detection

Position Overview

The role centers on serving as a quantitative expert to enhance fraud prevention measures. It involves analyzing transactional information to detect fraudulent activities, creating and refining machine learning algorithms tailored for fraud identification, and collaborating closely with engineering and product teams to deploy these solutions effectively. The position demands a balance of analytical acumen and business insight to stay ahead of fraudulent behavior.

Key Responsibilities

• Design, develop, and evaluate machine learning models for identifying fraud, ensuring ongoing oversight of model performance through monitoring and retraining.
• Conduct controlled experiments that assess the impact of fraud prevention strategies, weighing customer experience against minimizing financial losses.
• Analyze various fraud types and their effects on products to inform resource allocation.
• Create anomaly detection systems and heuristic approaches to detect emerging fraud trends early.
• Collaborate with fraud operations teams, developers, and product managers to transform model findings into actionable interventions.
• Investigate unusual data trends to identify new fraud methods and enhance model features accordingly.
• Explain complex technical trade-offs and experimental outcomes to stakeholders from diverse backgrounds to guide fraud strategy decisions.

Candidate Requirements

• A strong foundation in statistics or quantitative disciplines such as mathematics, engineering, or computer science.
• Minimum of three years’ professional experience in data science, risk analytics, or a related discipline with exposure to fraud or financial crime preferred.
• Documented experience deploying machine learning solutions in live production environments beyond exploratory analyses.
• Expertise in experimental design, statistical inference, model evaluation, and feature engineering.
• Proficient in Python and SQL, capable of managing the full model development lifecycle including deployment and maintenance.
• A proactive, investigative approach to uncovering subtle patterns and anomalies in data.
• Strong communication abilities for effectively conveying technical findings and actionable insights to both technical and non-technical audiences.
• Background or experience in fraud, risk, or financial services is advantageous, though related analytical experience is also welcomed.

Benefits and Work Environment

This role offers the opportunity to have a measurable impact on protecting millions of users from fraud. Candidates will join a dynamic team focused on collaborative, data-driven problem-solving alongside professionals in fraud operations, software engineering, and product management. The position provides a challenging environment to confront sophisticated financial crime issues while contributing to scalable, real-world solutions.

Additional Information

Location: Nairobi County, Kenya
Employment Type: Part-time, On-site
Qualification Required: Diploma or higher
Experience: Required; at least 3 years in relevant roles
Salary: Not specified; includes benefits
Note: Candidates should be cautious of fraudulent job offers requiring payment. This employer does not charge any fees during recruitment.