Senior AI / ML Fraud Specialist

To lead the integration of AI / ML technologies into telecom fraud management by combining deep fraud risk expertise with advanced analytics. The role will design, implement, and oversee next-generation fraud detection frameworks, ensuring protection against evolving fraud risks while safeguarding revenue and customer trust. Context / Background Fraud Management is a critical control function within telecom that mitigates revenue loss, protects brand image, and safeguards customer experience by ensuring : Fraud is minimized across all revenue streams, with effective prevention controls. Regulatory obligations and stakeholder expectations are consistently met. Traditional fraud management methods are enhanced with AI / ML-driven models to proactively detect fraud, adapt to emerging threats, and maintain compliance with industry standards. Role Accountabilities Overview Lead design and deployment of AI / ML-based fraud detection models for telecom fraud scenarios (e.g., SIM box, subscription fraud, roaming fraud, bypass fraud, OTT fraud). Drive innovation in fraud strategy through predictive analytics, anomaly detection, and automation. Configure, manage, and optimize Fraud Management Systems ( keep existing names

such as Subex, Mobileum, WeDo, or similar). Build, train, and maintain ML models for anomaly detection, predictive scoring, and automated alerts. Collaborate with IT, Data Warehouse, and Business stakeholders to integrate AI / ML into fraud monitoring tools. Mentor fraud analysts in advanced AI techniques and fraud risk management. Ensure regulatory compliance and industry best practices in fraud detection. Conduct shift-based monitoring (24x7x365) of fraud alerts and system activity. Evaluate new products / services for fraud risks prior to launch. Monitor audit logs and ensure effective audit trails on provisioning platforms. Distinguish fraud from bad debt and fine-tune Fraud Management Systems for accuracy. Analyze anomalies, identify root causes, and recommend resolutions. Develop preventive strategies and controls for emerging fraud risks. Provide fraud risk guidance across Billing, Credit Control, Sales, Customer Service, and Network functions. Business Impact Protect company revenue by reducing fraud-related losses. Build scalable AI / ML frameworks to future-proof fraud management. Enhance customer trust by minimizing fraud-related service disruptions. Costs & Profitability Costs borne by Fraud Management Department under Group Finance. Problem Solving Detect emerging and complex fraud schemes using AI / ML. Translate fraud risks into technical AI / ML solutions. Independently resolve fraud detection / prevention issues with strict timelines. Address both technical and business aspects of fraud control. Align fraud prevention strategies with IT, Data Warehouse, and Risk teams. Ensure timely fraud detection and closure of fraud issues without compromising quality. Use risk-based prioritization for new fraud threats. Key Relationships & Decision Making Mentor fraud analysts and act as Subject Matter Expert (SME) in AI-driven telecom fraud. Collaborate with OSS, BSS, IT, Marketing, Sales, Customer Service, Finance, OG, and RAFM functions. Communication & Influence Develop strong cross-functional relationships to achieve departmental objectives. Negotiate deadlines and align fraud prevention activities across departments. Decision Making Lead design and deployment of AI / ML fraud solutions. Influence investment in fraud management tools and AI platforms. Make operational decisions in fraud detection; escalate strategic issues to management. Key Performance Indicators (KPI) Identification of fraud risks and design of effective controls. Reduction in fraud-related revenue leakage. Accuracy, efficiency, and timeliness of AI / ML fraud detection models. Speed of detecting new fraud patterns. Cost savings through automation and optimized processes. Compliance with regulatory and audit standards. Timeliness and quality of fraud-related reporting. Experience, Qualifications & Skills Minimum Experience & Knowledge 10+ years in telecom fraud management covering multiple fraud types. Hands-on experience with Fraud Management Systems (Subex, Mobileum, WeDo, etc.). Deep knowledge of telecom technologies (GSM, LTE, 5G, roaming, interconnect, billing, mediation). Proven expertise in AI / ML (supervised / unsupervised learning, anomaly detection, predictive modeling). Minimum Entry Qualifications Bachelor’s degree in Telecommunications, Computer Science, Data Science, or related field. Advanced certifications preferred (AI / ML, CFE, CFCA, Data Science, or Fraud Risk Management). Technical Skills Big Data platforms : Hadoop, Spark, Databricks. Telecom fraud systems : Subex ROC, Mobileum RAID, WeDo RAID. Strong understanding of telecom OSS / BSS, IN nodes, provisioning, mediation, and billing systems. Non-Technical Skills Strong interpersonal and communication skills. Strategic thinking and innovation mindset. Leadership and mentoring capabilities. Seniorities Mid-Senior level Employment type Full-time Job function Finance and Information Technology Industries Telecommunications, Financial Services, and Technology, Information and Media Note : This refined description removes boilerplate and irrelevant items while preserving the original job information and context.

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