company-logo

Senior AI/ML Telecom Fraud Specialist

Description

We are seeking a Senior AI/ML Telecom Fraud Specialist to spearhead the evolution of our fraud management capabilities. In this critical role, you will lead the design, development, and deployment of advanced AI and machine learning models to combat a wide range of telecom fraud. Your deep expertise in both telecom fraud risks and advanced analytics will be pivotal in creating next-generation detection frameworks. You will drive innovation in our fraud strategy, leveraging predictive analytics and anomaly detection to protect company revenue and enhance customer trust. This position involves hands-on management of Fraud Management Systems, mentoring fraud analysts, and collaborating across business functions to integrate AI-driven intelligence. You will ensure our fraud controls are proactive, adaptive, and compliant with all regulatory standards. Join us to build a scalable, future-proof fraud management function that safeguards our assets and stakeholders against ever-evolving threats.

Requirements

1. 10+ years of direct experience in telecom fraud management, covering SIM box, subscription, roaming, and bypass fraud.

2. Proven expertise in designing, building, training, and deploying AI/ML models (supervised/unsupervised learning, anomaly detection) for fraud detection.

3. Hands-on proficiency with major Fraud Management Systems (e.g., Subex ROC, Mobileum RAID, WeDo RAID).

4. Strong programming skills in Python or R, along with advanced proficiency in SQL.

5. Experience with AI/ML frameworks such as TensorFlow or PyTorch.

6. In-depth knowledge of telecom technologies (GSM, LTE, 5G) and core OSS/BSS, mediation, and billing systems.

7. Experience working with Big Data platforms like Hadoop, Spark, or Databricks for large-scale data processing.

Desirable

1. Experience with cloud-based AI/ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.

2. Advanced professional certifications, such as Certified Fraud Examiner (CFE), CFCA, or certifications in Data Science or AI/ML.

3. Demonstrated experience mentoring and developing the skills of junior fraud analysts.

4. Proven ability to lead cross-functional projects and influence stakeholders in IT, Marketing, and Finance.

5. Experience conducting pre-launch fraud risk assessments for new products and services.

Getting StartedA few quick details so we know how to reach you

How did you hear about us? *

Which country's passport do you hold? *

Email *(Please ensure the email matches the one mentioned in your CV or resume)

LinkedIn Profile URL *

Please mention your notice period *

Let’s Get to Know You BetterA few short questions to understand your experience and what you enjoy doing

1. Do you have at least 10 years of experience in telecom fraud management? *

2. Have you led the full lifecycle of an AI/ML model for fraud detection, from design to deployment? *

3. Do you have hands-on experience configuring or managing Fraud Management Systems like Subex, Mobileum, or WeDo? *

4. Are you proficient in using Python or R for machine learning? *

5. Do you have a deep understanding of telecom OSS/BSS systems? *

6. Have you used Big Data platforms such as Spark or Hadoop in a professional capacity? *

Final DetailsSalary expectations and any supporting credentials
1. Where does your salary sit today (so we can help it move up tomorrow)?*

Enter your monthly salary in your local currency

2. What’s the number that’ll make you say "this is worth it"?*

Per month, in the currency mentioned

Upload ResumeHelp us get to know you better by sharing your most recent resume
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!
Something went wrong. Please try again later!