Data science Team Lead
Tasks
- Build fraud detection machine learning models
- Collaborate with engineering product security and data teams
- Define best practices for model serving feature engineering and experimentation
- Design offline AI evaluation frameworks
- Develop real time model serving systems
- Lead and mentor data science team
- Manage model performance latency scalability and explainability
- Monitor retrain and optimize model performance
- Own ML model lifecycle in production
- Tune models for customer specific environments
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Azure | Data Pipelines | Experimentation | Explainability | Feature Engineering | Feature Store | Fraud Detection | GCP | Kafka | Kubernetes | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model Serving | Model Training | Model Tuning | Model retraining | Observability | Offline evaluation | Python | Real Time | Real-time Inference | Spark | Stream processing
Education
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