ML Researcher

Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress Managing available resources such as hardware, data, and personnel so that deadlines are met Analysing 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 distribution that could affect performance when deploying the model in the real world Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Defining validation strategies Defining the pre-processing or feature engineering to be done on a given dataset Defining data augmentation pipelines Training models and tuning their hyper parameters Analysing the errors of the model and designing strategies to overcome them Deploying models to production