๐Ÿ”ฅ Matt Dancho (Business Science) ๐Ÿ”ฅ
๐Ÿ”ฅ Matt Dancho (Business Science) ๐Ÿ”ฅ

@mdancho84

12 Tweets Jan 05, 2023
The problem with the #datascience hiring process. ๐Ÿงต
#rstats
You might see graphics like this one that I'm about to show you.
It's what I teach in my upcoming course. And it's very accurate.
But there's a problem.
The problem is that each step is a landmine that when stepped on will cost you extra weeks or months.
Those missteps add up, which is why many data scientists report that it takes 9-months or longer to get a job (after they complete their education and are fully qualified).
9-months may not sound like a lot, but if we were a business, no income for 9 months equals 75% of a year's salary, which is about a $75,000 cost even for an entry-level data science position.
To make matters worse, you have rent, bills to pay, food and gas, plus inflation is driving everything up.
So time is of the essence.
And speed is important.
And you need to avoid missteps in the process if you want to get a data science job quickly.
So here's 2 quick tricks.
1. Don't apply in quantity (apply for quality)
Most people think in terms of quantity. But it's the opposite when you apply to jobs.
I heard a story of a data scientist applying to 500 jobs over 9-months and not landing any interviews.
The problem was she was applying to every company through their application system and then sending her basic resume to every single company.
2. Don't skip referrals
99% of job applicants apply online and hope their resume get's picked for an interview. It might surprise you, but...
You have less than a 1% chance of getting an interview this way
A better approach is to come in referred.
Why?
If you come in referred...
There is a 99% chance you get an interview.
Want to learn more about how to get a data science job fast?
I spent 1-year studying it, and I'm revealing all of my secrets during my 2-hour LIVE course launch event.
You can register here: bit.ly

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