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.