Description : Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability,
Exploring and visualizing data to gain an understanding of it, then identifying differences in data a distribution that could affect performance, when deploying the model in the real world,
Verifying data quality and/or ensuring it via data cleaning
Finding available datasets online that could be used for training
Defining validation strategies
Defining the preprocessing or feature engineering to be done on a given dataset,
Defining data augmentation pipelines,
Training models and tuning their hyperparameters,
Analyzing the errors of the model and designing ,
Number of Openings: 3