Definitely not. Let me put things in perspective.
There are two types of companies, Company A - statisticians working as Data scientists, good engineers deploying models in production.
Company B - have no clue what ML or AI is and feeling the heat. They could be a multi million dollar company or a small SMB.
You will always find both these A & B atleast until ml and AI is well democratised. It is not, not even close. We are at the early stage of the curve still, but moving forward there will be rapid growth in the next 5-8years.
You have few options:
1. Start with sql. It’s not hard, join as an analyst and learn to code. Make sure the team or product you join deploys models.
2. Learn basic python and some orchestration tools (airflow, spark or aws/azure equivalent) . Join as data engineer along with basic sql skills.
I dont think I've been to two companies that had the same or even similar definition of 'data science'. Often it meant something like: see if you can use Tableau to produce new insights.
Absolutely this. My side of the engineering department has taken a hard stance on what our definitions of Data Analyst, Data Engineer, Data Scientist, Machine Learning Engineer and Applied Scientist are. We have had a few issues with people wanting a different job title while interviewing and we supply them with our description plus a path from the position we believe they are to what they want to be. The ones who have taken these offers have been some of our best hires.
On the other hand the analytics/sales teams have many DS and MLEs, a DA is basically a “junior” for them, but they routinely have to reach over to an engineering team to do pretty basic SWE skills that they are supposed to cover themselves
Company B - have no clue what ML or AI is and feeling the heat. They could be a multi million dollar company or a small SMB.
You will always find both these A & B atleast until ml and AI is well democratised. It is not, not even close. We are at the early stage of the curve still, but moving forward there will be rapid growth in the next 5-8years.
You have few options: 1. Start with sql. It’s not hard, join as an analyst and learn to code. Make sure the team or product you join deploys models. 2. Learn basic python and some orchestration tools (airflow, spark or aws/azure equivalent) . Join as data engineer along with basic sql skills.