5-Year Data Scientist Struggles with Transition to Marketing Data Science

A Senior Data Scientist with 5 years of experience in Applied Data Science, focusing on machine learning (ML) and deep learning (DL) models, has recently transitioned to Marketing Data Science. This shift involves tasks like designing experiments, analyzing causal impacts, and media mix modeling, areas where the scientist admits to having less expertise, particularly in Bayesian models and causal inference. The scientist notes that in this new role, the work often involves quickly addressing business questions with presentations that are just one or two slides long, which feels less impactful compared to their previous work. Despite innovative solutions, traditional business practices often prevail, leading to a sense of demotivation and a lack of perceived impact in their new role. This experience raises questions about the commonality of such feelings in the product data science and causal inference fields.

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