Requirements

• 2+ years of experience of working on cloud platforms (AWS, Azure or GCP) and using cloud-native ML services
  
• Ability to create efficient solutions to complex problems. Strong skills in data-structures and Machine Learning algorithms
  
• Experience of working on end-to-end data science pipeline: problem scoping, data gathering, EDA, modelling, insights, visualizations, monitoring and maintenance.
  
• Ability to develop, test, and deploy models on cloud / web
  
• Strong understanding of mathematical, statistical, and theoretical foundations of statistics and machine learning
  
• Ability to learn new tech stacks and tools in data science and put them to practical use
  
• Problem-solving: Ability to break the problem into small parts and applying relevant techniques to drive required outcomes
  
• Working experience of building and deploying 3-tier, cloud-native applications
  
• Strong understanding of data structures and programming concepts
  
• Experience in working with Linux computing environment and use of command line tools
  
• Good grasp on databases including RDBMS, NoSQL, MongoDB etc.
  
• Working experience of cloud-native ML services like AWS SageMaker, Azure Machine Learning and GCP AutoML etc.