Product Managers (PdM) work with product lines, since they are allotted one of them and they deal with its profitability. In the particular case we are approaching, the PdM will manage the growth in profitability of technical applications regarding product lines. In this field, the data science PdM requires technical knowledge.
This technical knowledge does not mean they need to be data scientists, but they are expected to recognize and categorize the different kinds of business with ease, together with the technical challenges which could be settled through data science or machine learning.
The requirements that a PdM must have are a deep understanding of mathematic modelling and firm familiarity with former applications. By way of example, in the case of a product line with an image recognition element, the data science PdM would be expected to know that convolutional neural networks (CNNs) are a useful solution in these kinds of business issues.
On the other hand, there is no need to know all about the most recent advances in generative adversarial networks (GANs) or in abilities to implement a CNN, just an insight on identifying the right types of problems so that the data science team of professionals can deal with them.
However, the solutions that the data science team makes must be endorsed as well by the stakeholders and executive decision-makers. In the case of data scientists recommending the use of GANs for image classification, the PdM requires translation abilities in the aspects of reading, understanding and interpreting the supporting research underlying in the recommendation.
Then, after translating the underlying information, a data science PdM will need to transfer all the research into a comprehensible presentation for non-technical people, so that they can be able to make decisions about the recommendation.