During my recent job hunt I realised that there are lots of blogs out there highlighting the differences between Data skillsets (Analyst, Data Scientist, Machine Learning Researcher etc). However, I didn’t come across many that explore how these skillsets tie in with different business functions of a company (Marketing, Product, R&D etc).

Many of the roles I came across had the same titles but the requirements and responsibilities of the roles were completely different. Making this connection between data skillset and business function not only helped me classify the different roles I discovered but also helped me understand how I wanted my career to progress. I created a framework to help with this and I wanted to share it with other budding Data Professionals that want to understand the differences between the skillsets required and the business problems that each role would focus on.

The other thing that I experienced was that there is sometimes a gap in understanding of the role between recruiters/hiring managers and applicants. This gap often isn’t highlighted until the 2nd or 3rd stage of the interview process. So I guess this post could also help hiring managers and business owners better understand what kind of Data Professional they are seeking, and in turn be able to convey that in their Role Spec, resulting in higher quality applicants and less time wasted for everyone.

#data #big-data-career #recruitment #data-science