At Kyso (https://kyso.io) we see a lot of people get hired into data-science jobs and the biggest success factor that I've personally seen is having some example's of projects that the candidate has worked on. This can be either public projects online (thats what we started Kyso to help with!) or a description of a project they worked on while studying/working.
Something I've noticed about data-science candidates is that they are very happy to jump into the technical details of an implemented model - but sometimes struggle on is communicating the reasons for the model in the first place and how it can help the company/research project. A lot of data-science projects are smaller ad-hoc jobs where the data scientist is trying to answer some business question and here communication is a vital skill.