When executed effectively, data science solutions for enterprise applications can achieve a rinse-and-repeat quality, meaning the process for updating or extending a solution (such as for a new business cycle) becomes streamlined and repeatable. However, reaching this level of maturity is challenging. It usually takes a few iterations to arrive at something worth repeating and improving. This takes experience, skill, and an understanding of your business dynamics. Getting to this point definitely involves making the right technical choices, but it also requires developing a deeper understanding and intuition about your data, use case, and how they relate. Descriptive Analytics has the tools for this, and this is what I can help you with.
I am a seasoned data scientist. Please see this link for a professional summary and published work (including my Google Scholar profile). Here are samples of the kinds of analyses I can do for you. If you have a business task that you want to augment or implement with data science, I would appreciate a conversation to explore whether this task falls within my wheelhouse. I have also developed a simple open-source tool to document and maintain analytics and machine learning projects.
Ready to move from ideas to implementation?
If you have a business-critical use case in mind, let’s evaluate it together and define a practical first iteration.