Researchers think mechanistically about the world

What do we mean by "thinking mechanistically"? This refers to being able to think mechanistically through data generating processes. In research data science, this likely requires a deep knowledge of the field that one is applying quantitative methods to, i.e. domain expertise. Though deep domain knowledge is usually correlated with doctoral training or many prior years of work experience, a newcomer can compensate for domain knowledge deficits by demonstrating the skill of being able to learn domain knowledge really quickly, or by having complementary breadth of modelling knowledge that has been honed in a diverse set of settings.

For someone who has not yet had the domain expertise to think mechanistically about a problem, they need to Learn how to learn fast.

Learn how to learn fast

How do we learn how to learn fast?

I can mostly only speak for myself, and even then, I know I'm not the fastest learner. But some principles come to mind, which appear to have been battle-tested.

  1. The first is to Build a project portfolio.
  2. The second is to Learn like Feynman.
  3. The third is to Learn adjacent topics, rather than distant ones.

The end goals of research data science

What are the end goals of research data science?

One of them is being able to explain the world, ideally in a causal fashion. (See: The goal of scientific model building is high explanatory power)

The kind of data scientist we need for this kind of work is different from that of business data science (see: The end goals of business data science).

The context in which research data science operates is one where business processes (and their corresponding business outcomes) are oftentimes not well defined. Thus, defining the ROI is a less straightforward task than it might otherwise be. As such, we need to view research data science as an investment for the future, just like any research organization is.

Also a thing to read: Researchers think mechanistically about the world

State of Data Science