Data Scientist
 

Key Responsibilities

  • Develop and deploy scalable machine learning systems in production environments
  • Build efficient data pipelines and infrastructure for AI applications
  • Optimize ML models for performance, reliability, and scalability
  • Implement MLOps practices for continuous integration and deployment of AI models
  • Ensure AI systems meet banking security, compliance, and performance requirements
  • Collaborate with data scientists to translate models into production-ready code
  • Design and implement monitoring systems for deployed AI applications
  • Troubleshoot and resolve issues with AI systems in production
  • Contribute to the development of internal ML platforms and tools
  • Stay current with latest developments in ML engineering and MLOps

 

Experience: 4 to 11 years of experience

 

Required Skills
 

  • Strong programming skills in Python, Java, or similar languages
  • Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
  • Knowledge of containerization and orchestration tools (Docker, Kubernetes)
  • Experience with CI/CD pipelines and DevOps practices
  • Understanding of software architecture and system design principles
  • Familiarity with cloud platforms (AWS, Azure, GCP)