> We strive to lead the business with our output rather than to inform it I think the business hires data scientist to be informed. Not to make business decisi

> We strive to lead the business with our output rather than to inform it I think the business hires data scientist to be informed. Not to make business decisions on their behalf. > Data scientists love working on problems that are vertically aligned with the business and make a big impact on the success of projects/organization through their efforts. They set out to optimize a certain thing or process or create something from scratch. These are point-oriented problems and their solutions tend to be as well. They usually involve a heavy mix of business logic, reimagining of how things are done, and a healthy dose of creativity Again, I'm confused? That sounds like the data scientists should have majored in business then. If data scientists start doing that, what will all the other business folk do then? Data scientists should just build out reports that provide valuable insights and potential patterns that can help make business decisions. The difference with prior reports engineer or data analysts or wtv, is that a data scientist is assumed to be able to generate statistical analysis or/and pattern analysis over the data. While prior, a data analyst only needed to perform basic versions of that which did not go beyond what SQL could do. The data engineer should enable the data scientist to perform this analysis by both working with the software engineers to acquire it safely, securely, reliably and at scale. And working witj the data scientist in order to apply his statistical analysis efficiently and at scale to a possibly very large data set. Finally, he might need to work with both software engineer and data scientist to setup real time or close to real time versions of the analysis. All result from the analysis should be presented (aka reported) to the business. The data scientist can suggest interpretations or ideas to address findings, but it's the business role to make tactical and strategic decisions about business processes and products. And if you're doing ML as part of a process, then you need a ML scientists. Say you need to build out voice recognition, or the likes. Basically comp sci or math majors with ML masters or PHDs.