Job descriptionUnderstanding business objectives and developing models that help to achieve them, along with metrics to track their progressManaging available resources such as hardware, data, and personnel so that deadlines are metAnalyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probabilitySupervising the data acquisition process if more data is neededExploring 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 worldVerifying data quality, and / or ensuring it via data cleaningDeploying models to productionFinding available datasets online that could be used for trainingDefining validation strategiesDefining the preprocessing or feature engineering to be done on a given datasetDefining data augmentation pipelinesTraining models and tuning their hyperparametersAnalyzing the errors of the model and designing strategies to overcome them