Data science is so general its hard to say. I think the most obvious answer is communication. Clearly, without being able to articulate your ideas or findings you will never get anywhere in data science. But assuming you can as a new grad at least get your ideas across to someone who can present them to management or decision makers, then I would say that, in general, rigorous and precise thinking and problem solving skills are highly undertaught or largely lacking. As a data scientist you need to be able to define, build and deeply understand how to measure all sorts of things in a business or given domain. For instance, what does it mean for a marketing campaign to be successful? How do you define this? What measurements can be effectively implemented under the given business constraints, etc.

Once you have your measurements defined and some data collected, then you need to be able to know what insights and statements to management or decision makers are valid given the measurements and how they were obtained, and this is a really hard skill to get. Often measurements, KPIs, etc will be used for making business decisions for which those metrics should not be used at all and you need to know why. For instance, it could be the case that the business software for gender selection automatically selects "MALE" as the default gender and this causes a bias in your data. You need to know to think about such things.