The Fraud Risk Analytics role analyzes and mitigates fraud risk within the organization's e-commerce platform.
This involves identifying, monitoring, and responding to fraud patterns and trends from customer and merchant perspectives. The role requires a strong analytical mindset, technical skills, and domain knowledge of the e-commerce and payments industry.
Key Responsibilities:
• Develop robust fraud detection models and algorithms to identify real-time fraudulent activities within the e-commerce ecosystem.
• Analyze e-commerce transaction data, customer and merchant behaviors, and other relevant information to detect anomalies and suspicious patterns.
• Collaborate with cross-functional teams (e.g., risk operations, compliance, e-commerce operations) to investigate and resolve fraud cases impacting customers and merchants.
• Continuously enhance fraud detection capabilities by incorporating new data sources, machine learning techniques, and industry best practices tailored explicitly to e-commerce fraud.
• Generate insightful reports and dashboards to provide visibility on fraud trends, KPIs, and the effectiveness of fraud mitigation strategies within the e-commerce platform.
• Stay up-to-date with emerging e-commerce fraud schemes, regulatory changes, and industry benchmarks to proactively adapt the organization's fraud prevention measures.
• Provide subject matter expertise and recommendations to stakeholders on e-commerce fraud risk management strategies.
• Assist in implementing fraud control frameworks, policies, and procedures to protect customers and merchants from fraud risks on the platform.
Requirements
• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 3-5 years of experience in data analysis, predictive modeling, and fraud detection, preferably in the e-commerce or payments industry.
• Strong SQL, Python, and/or proficiency for data manipulation, analysis, and model development.
• Hands-on experience with machine learning algorithms, statistical techniques, and data mining tools, focusing on e-commerce fraud.
• Thorough understanding of the e-commerce ecosystem, fraud typologies, and industry regulations.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Ability to effectively communicate technical findings to both technical and non-technical stakeholders.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is preferred.
