Data Sciencists are valued for their power, and their ability to have skills that overlap different areas such as business development to software development. However, this also leads to an expectation mismatch, where you might have thought of working on building algorithms but end up building simple dashboards for business requirements, eventually hampering your performance.
This is what I suggest:
- Make a full list of skills you think a data scientist may work on.
- Shortlist the list, to three categories, one that you are good at, two you are picking up but you’d like working on it, three you have never worked upon, or have no clue about.
- Don’t apply based upon job titles, but seek detailed JD from recruiters.
- The JD should include roughly less than 30% of category 2 skills and less than 5% of category 3 skills.
Remember that, it’s better to get rejected than to land yourself in a place that is a total misfit, especially for people with less than 2 years of experience.