The most common complaints we see from candidates who have faced rejection are lack of experience, education level requirements, inadequate opportunities for newbies, and overly demanding and confusing requirements for the job.

Across professions, it’s a common complaint that employers for entry-level jobs seek applicants with years’ worth of experience.

Every company wants a seasoned data scientist, but with the rapid emergence of the field and growing demand for professionals, there’s just not enough to go around.

You can also build experience outside a business setting in a way that a hiring manager will notice.

For instance, you can join Kaggle competitions (the world’s largest community of data scientists and machine learners), write code, and that put that on GitHub (which provides free plans for open-source projects and paid plans offering unlimited private repositories) for people to see.

Perhaps you can also offer free consultations for coding and analysis to friends or businesses.

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