I'm reading a lot of sour grapes here, but I'd like to offer a more optimistic future snapshot (if you're a data scientist and happen to be reading).
I agree that many companies hire data scientists with only a vague idea about how to utilize them, but the same is true of software people in general. "Software is eating the world" and so is the practice of extracting value from data.
The margin on software is high - often more than 95% - so there's a lot of room to screw up and "figure it out" as a business. I think that's why there's a low bar for software and data management compared to, say, an automotive manufacturing line manager.
But that's where the opportunity is, if you're a budding data scientist:
- The business might not know how to effectively use/manage/train/mentor you.
- Upper management might have 20+ years of line of business experience, but will need your help to understand how your team can impact the business.
- You're going to need to seek out ways to impact the bottom line of the business.
All of the above is a recipe for leaping forward in your career. Since data science is a relatively new field, the demand for senior leadership FAR outstrips the available supply.
If you can learn how to effectively manage yourself, your team mates, and your function within the business - you have a ton of negotiating leverage and can name your price.
Source: I'm a data person who "retired" in their early 30s. Now I do all the research and hard science I want. ;)
> the demand for senior leadership FAR outstrips the available supply.
This is so very, very true. Most of the "bad" data science orgs I've spent time with, are bad because leadership is either bluffers or a data engineer/BI type person. It's generally hard for these types to run effective DS orgs as the skills needed are very, very different.
I agree that many companies hire data scientists with only a vague idea about how to utilize them, but the same is true of software people in general. "Software is eating the world" and so is the practice of extracting value from data.
The margin on software is high - often more than 95% - so there's a lot of room to screw up and "figure it out" as a business. I think that's why there's a low bar for software and data management compared to, say, an automotive manufacturing line manager.
But that's where the opportunity is, if you're a budding data scientist:
- The business might not know how to effectively use/manage/train/mentor you.
- Upper management might have 20+ years of line of business experience, but will need your help to understand how your team can impact the business.
- You're going to need to seek out ways to impact the bottom line of the business.
All of the above is a recipe for leaping forward in your career. Since data science is a relatively new field, the demand for senior leadership FAR outstrips the available supply.
If you can learn how to effectively manage yourself, your team mates, and your function within the business - you have a ton of negotiating leverage and can name your price.
Source: I'm a data person who "retired" in their early 30s. Now I do all the research and hard science I want. ;)