Following advices I offer:
Job role clarity: Be clear on what your strengths are and apply just there!
For example, A title can be data analyst, but it’s important to check their JD out! It it’s demanding intense ML, and if you’re not ready for it, skip it rather than burning out.
- Patience: Finding a job is like match making for both the parties. There’s more than just the technical skills that the interviewer is looking at. As a best practice, only tweak 5-10 % of what you are for the requirements, rest be the way you naturally are. If you’re a good fit, you’re in. And, there’s a role for everyone, somewhere out there. You just need 1 good job, not 100. So hang on!
- Learning the right skills: Keep learning from every interview. Hone the skills needed. Update the capstones if needed.
- Showcase the right project: When interviewer asks, describe your capstone project. Remember to pick the one that is closes to the JD! Also add nuances to your analysis that make you stand out. It could be simple things such as your own crafted ML feature or way you did missing value treatment than just a simple mean.