# Decision Journal - Product Data Scientist vs. AI Engineer Role ### Information to still gather * Talk to Michael about what I would exactly be doing * Talk to Reed about the role, growth, etc * Look at recent PRs from Reed, Tom * Fill this out https://fscourses.s3.ca-central-1.amazonaws.com/Decision+by+Design+/Bonus+Content/decision-journal_template.pdf ### Key areas of focus * Will it be challenging be on a more ego driven team? Following JW? * What would *prevent* me from taking the AI Engineering role at this point? * If I gathered information that would make me confident I would hate it * Note: I don't expect that *long term* I want to be an AI engineer. Long term I want to consult. Generally, to consult you want to be very general. Imagine this: A client wanted me to consult on solving a complex problem for them. I needed to access their data via large instance on AWS. Learning K8s, postgres, ssh, cloud infra, and so on, will be incredibly useful for these purposes. I don't need to be an expert by any means, but continuing to learn and understand them will likely be good * Stopping Function: End of this week. I should have been able to gather enough information by then. * Note: The AI Engineering team is likely even *more* technically impressive than DS team (i.e. Tom and JW). Learning from them would be powerful. ### Most Important Thing > Grow a technical skill set that is *wide* and *deep* (in at least two areas) so that I am in a position to eventually open a *consultancy* or operate as a *CTO*. This requires that I keep *growing rapidly*. ### This *and* That A key question to ask myself during this is how can I do *this* and *that*? Is there any way to remain involved with the DS team to any capacity? Is there a way to ensure that I could come back at some point if the role isn't for me? ### Opportunity Cost * Remaining a DS * More of a leadership opportunity compared to AI Engineer. Potentially a greater chance to be super innovative compared to AI engineer. * At the expense of moving into a role that would be *very* different than any role I have ever had, learning more about product, what it takes to differentiate in the tech world, what it takes to generally solve problems, and so on * Switching to AI Engineer * More technically challenging, less innovative. Harder to get this role given current skill set. More technical growth in areas that it would be good for me to continue growing in. * At the expense of leadership on DS team and be a innovative force. ### What is the problem? * I have an incredible role right now on the data science team and have quickly become one of the most valuable contributors * In this role I have been at my most innovative and experienced more growth than ever before * Staying in this role I can continue to grow into a leader and key innovator for the company. In this role I am likely more useful to the company on the whole. * In the AI Engineering role I have the opportunity to learn an entirely new field and set of skills * It will likely be the role that pushes me to grow more technically * I would continue to be surrounded by great problem solvers, and be exposed to the product side of the business, seeing what it takes to build an AI system that scales and is robust * This type of a role would give me more ability to eventually be a CTO some day, as well as a consultant * AI engineer role is likely one that would be *very* hard to get if I was simply interviewing from scratch * The problem is: How do I chose between these two roles?