Build machine learning models in open-source packages like Python and deploy using cloud infrastructure available in AWS Sage maker Azure ML flow.
Understand the business requirement and suggest evaluating the right features and technique best suited to train and test the model.
Work on feature engineering to ensure most information going into the model for prediction accuracy.
Work with cloud architecture and digital development team to deploy the model online and offline.
Work with testing team to design the test online or offline and work towards improving the model based on test results.
Collaborate with internal stakeholders to understand the business strategy and work towards supporting that by gathering the right data and building machine learning models.
Follow machine learning model management and lifecycle best practice for all Artificial Intelligence and Machine Learning models created.