There is a tremendous amount of active research in making deep learning models interpretable (e.g., LIME and Layer wise Relevance Propagation). In summary, a high accuracy data science component by itself may not mean much even if it solves a pressing business need. On one extreme, it could be that the data science solution achieves high accuracy at the cost of high compute power or high turnaround time, neither of which are acceptable by the business. On the other extreme, it could be that the component that the end-user interacts with has minimal sensitivity to the errors of the data science component and thus a relatively simpler model would have sufficed the business needs. A good understanding of how the data science component fits into the overall end-to-end solution will undoubtedly help make the right design and implementation decisions.

Managing stakeholders in the world of data science projects is a tricky prospect. I have seen a lot of executives and professionals get swept up in the hype around data science without properly understanding what a full-blown project entails. And I don't say this lightly – my career has been at the very cusp of machine learning and delivery. I hold a Ph.D. in Data Science and Machine Learning from one of the best institutions in the world and have several years of experience working with some of the top industry research labs. I moved to Yodlee, a FinTech organization, in 2016 to run the data sciences product delivery division.

You're in good company – a recent article by Laurence Bradford in Forbes calls data science'the century's hottest career'. But how can you get your foot in the door? Many resources out there may lead you to believe that becoming a data scientist requires comprehensive mastery of a number of fields, such as software development, data munging, databases, statistics, machine learning and data visualization. You don't need to learn a lifetime's worth of data-related information and skills as quickly as possible. Instead, learn to read data science job descriptions closely.