Requirements
1. 10+ years of experience in telecom fraud management, covering diverse fraud types like SIM box, subscription, and roaming fraud.
2. Proven expertise in designing, building, and deploying AI/ML models (supervised/unsupervised learning, anomaly detection, predictive modeling).
3. Hands-on experience configuring, managing, and optimizing commercial Fraud Management Systems (e.g., Subex, Mobileum, WeDo).
4. Proficiency in AI/ML programming languages and libraries such as Python, R, SQL, TensorFlow, and PyTorch.
5. Experience with Big Data platforms like Hadoop, Spark, or Databricks for processing large-scale telecom datasets.
6. Deep knowledge of telecom technologies (GSM, LTE, 5G), network architecture, and core operational/business support systems (OSS/BSS).
7. Demonstrated ability to manage the full AI/ML model lifecycle, including training, validation, deployment, and maintenance.
8. Strong understanding of telecom billing, mediation, provisioning, and interconnect systems and their associated fraud risks.
Desirable
1. Bachelor's degree in Telecommunications, Computer Science, Data Science, or a related technical field.
2. Advanced professional certifications in AI/ML, Data Science, CFE (Certified Fraud Examiner), or CFCA.
3. Experience with cloud-based AI platforms such as AWS SageMaker, Azure Machine Learning, or Google AI Platform.
4. Proven leadership and mentoring skills with experience guiding junior analysts.
5. A strategic and innovative mindset with the ability to translate complex fraud risks into technical solutions.