The data science professionals my company has had on staff have been a joke. It’s similar to the wave of inexperienced developers hired in the late 1990s; employers didn’t have the skills to prove that the contractors didn’t know what they were doing, so a ton of money was poured in with big dreams.
Part of that is that they don’t understand what we do and weren’t trained. They other part is that the business was just told they needed data people.
What businesses need today are to understand what they’re interested in first, and then hire people with proven experience and knowledge to accomplish those goals.
Having a PhD in any applicable subject in addition to sufficient practical knowledge of data science, machine learning, and AI would be a substantial plus for a niche position in the industry, a non-profit, or even in finance.
This is key. What do companies actually want when they hire a data scientist? Actionable products that make their business better.
What does it take to produce actionable products? A data strategy (collection, ingress, normalize, enrich, store, expose), a compute provisioning strategy, data engineering (pull from source system(s), land in target stores in a reliable, available, automated manner), data science, and data application (reporting, integration with target systems, app development).
Which of those components do they typically have? A data scientist. Because they just hired one.
Career-wise, the more unifaceted your skillset is, the more you're limited to employers that already have all the other pieces in place. Which effectively limits you to very large enterprise (~T100).
Start to be able to fill some of the other roles yourself, and you can compete for and succeed in smaller and more interesting opportunities.
Part of that is that they don’t understand what we do and weren’t trained. They other part is that the business was just told they needed data people.
What businesses need today are to understand what they’re interested in first, and then hire people with proven experience and knowledge to accomplish those goals.
Having a PhD in any applicable subject in addition to sufficient practical knowledge of data science, machine learning, and AI would be a substantial plus for a niche position in the industry, a non-profit, or even in finance.
Don’t give up.