Must have skills:
8+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.
Experience in designing and developing scalable predictive models to address dynamic pricing, price promotion challenges and optimizing pricing strategies.
Experience in implementing A/B testing to evaluate the effectiveness of different pricing strategies.
Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Hands-on experience on AWS Machine Learning services. Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs.
Implement and manage MLOps principles and best practices for ML architecture.
Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc.
Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.
Good to have skills:
Experience in dynamic pricing, price promotion and price optimization.
Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.
Experience with software development.
Able to effectively design software architecture as required
Any Graduate