Statistics, ML, AI and what not!
Data science: The big picture and why you should care
In a previous post, we discussed broadly what kind of profiles exist in the market around data. Specifically, we discussed what the profiles ‘Business Analyst’, ‘Data Scientist’, and ‘Data Analyst’ mean. We also promised that we’ll later discuss how to pick a position in a company to apply for. So here we are!
Companies are not consistent in their terminology
Indeed, one of the primary reason for all the confusion around these profiles is that companies have been using these terms rather arbitrarily as they see fit, leading to a lack of a standard definition of these roles. For the same kind of role, the job titles are different across industries and companies.
There are several different roles/job profiles: Business analyst, Marketing analyst, Machine learning specialist, Data scientist, Decision Scientist, Product Analyst, Marketing analyst and many more.
The role of a data scientist at a company like LinkedIn is poles apart from that of a data scientist at, say, Flipkart. Also, the same profile may be called a data scientist at one place, a business analyst at another.
So which role should you apply for?
First, ask yourself which of these roles is aligned with your aspirations. Meditate on this and be clear on which profile you want.
When applying to a company
Follow the simple steps below –
Ask them what a typical day at the job would be and what the expectations from the role are.
At this stage, disregard completely the title being used by the company.
With your understanding of the role, map it to one of the three profiles we understand.
Then, and only then, decide whether you want to go forward. Don’t make the mistake of getting into an unsuitable profile just because the title sounds attractive. I hope this little guide clarifies things and helps you take the right first steps.
All the best!