Software products can be layered into 3 parts - - data collection (frontend, APIs) - data storage (database, backend) - data visualization (dashboards, analyti

Software products can be layered into 3 parts - - data collection (frontend, APIs) - data storage (database, backend) - data visualization (dashboards, analytics, reports) To bootstrap a startup, the primary people you need would be - a frontend person, a backend person, and a product person. In the beginning, you would be dreaming about the possibility of using ML but would not invest in hiring a data scientist at that stage. The second stage would be to hand over the reins to operations people and let them optimize the internal and external processes and get ready for the launch (growth). These phases can take-up any amount of time, from 2 to 5 years. Finally you handover the reins over to the salespeople and go back from product to services mode (especially true for enterprise software). During this stage, you would be hiring a data scientist and a team of data analysts. After, around 6-8 years of bootstrapping a company. Unless your product relies heavily on the ML algorithm, it can and would always wait. Figuring out where to first use ML is another challenge. Hiring a data scientist and ask them to tell you what to do is a futile effort. ML is a useful tech and if you have to keep thinking about utilizing this technology to improve your product and processes. It has to be a part of your long term efforts.