In order to develop algorithms, data scientists must have an in-depth understanding of Statistics and its various components. This skill set is critical for training effective models; for example, it enables them to select optimal features from large datasets and employ appropriate sampling techniques when dealing with scarce data.
Additionally, knowledge of probability theory helps create more reliable estimations by providing the basis for assessing uncertainty in predictions.
Using sophisticated mathematical techniques such as regression analysis and clustering, data scientists can uncover new insights from raw data that would otherwise remain hidden away forever.