You will lead AI initiatives that directly impact millions of telecom subscribers and fintech customers — from predicting churn and personalising offers to detecting fraud in real time across payment networks.
ROLE MISSION
Lead delivery of production-grade AI solutions using Microsoft Azure AI, Fabric, and Azure ML.
SUCCESS IN FIRST 90 DAYS
- Lead 1–2 AI MVPs to delivery
- Define reusable feature engineering patterns
- Establish model lifecycle standards
Key Responsibilities
- Lead ML model design and deployment for telecom use cases including churn prediction, network anomaly detection, and customer lifetime value modelling
- Guide feature engineering on Fabric/Databricks using telecom CDR data, customer behaviour signals, and financial transaction records
- Build and deploy AI models for fintech use cases including fraud detection, credit risk scoring, and payment anomaly detection
- Mentor junior data scientists and set technical standards for model development
- Integrate with Azure ML and AI Foundry to establish repeatable, production-ready ML pipelines
Must-have Skills
- Python and ML frameworks (scikit-learn, TensorFlow, PyTorch)
- Azure ML
- Feature engineering at scale
- MLOps concepts and model lifecycle management
NICE-TO-HAVE
- Experience with telecom CDR or network data
- Background in fintech fraud detection or credit risk modelling
- Azure AI Foundry or AI Services experience
- Generative AI and LLM integration experience
