With only heavy statistical background professional have proper experience in this domain and recruiters should hire data scientists, who have a rich and strong background and capable to do their job. You can do data science without statistics, Data science without statistics is possible, even desirable
If you spend 80% of your time cleaning data, you are not a data scientist. Data science is about automating these boring tasks. And automating much more advanced tasks. Everything you learn in a book will eventually be outsourced to robots or automated, be it logistic regression or SVM. If you haven't made at least $150k/year for 5 years in a row doing data science by the time you are 40 years old, then maybe your "data science" activities are not producing the great value you believe they do.
If you don't trust your intuition or gut feelings to some extent, either you know your intuition is not reliable (and that's great to admit it), or you are missing a big part of data science. Data science is a science, and an art. Many calling themselves data scientist today are neither scientists or artists.
If you don't have success stories in your portfolio, where you can prove that you helped save or generate $1 million in revenue out of data (including finding the right data, asking the right questions to stakeholders to clarify problems in the first place, and get your POC deployed in production mode) then you are not a data scientist. There is no such thing as a junior data scientist.
Think about this: are you ready to play on the stock market for real, risking your own money, and use data science strategies to beat everyone else? You would be playing against very sophisticated data scientists. I did it, also in the real estate market including when everyone got squeezed, and I did not use statistical models, linear or logistic regression in any way to succeed.
Visualizations are great. Anything that communicates in 30 seconds what others would communicate in months, is like magic.
In real estate with having this motto location, location, location. My motto in data science is simplicity and automation. If you are searching for the perfect model, just like some people were searching for the philosopher's stone a while back, you are wasting your time and wasting your CEO's money.
Know the 80/20 rule, you can get 95% of what you can achieve with a simple solution designed in a week than you could get after spending two years on the same project. Do that all the time, it is incredible how much you could accomplish following this rule, and the return you would get especially, as in my case, you have no boss and all your revenue / added value depends on how efficient you are at generating it.
You can not successfully design automated data science without significant experience and training.
Deploying automated data science is just like climbing Everest solo in winter with no oxygen. What some people call data science nowadays is climbing Everest without any mountain experience, helped by 100 Sherpa and guides who will lift you to the summit even if you are sleeping. That comes with a cost, when it comes to data science: negative ROI, unable to detect fake news, and more.