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- New jobs in sports analytics! Measuring the impact of the analytics department.
New jobs in sports analytics! Measuring the impact of the analytics department.
9 top tier data science opportunities for you this week!

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🚀 Jobs metric: 116 new jobs in the last two weeks!! 🚀
New jobs is Sports
This edition is full of opportunities. We have been uploading several data science, analytics and data engineering jobs in great teams and organizations. So many that I couldn’t pick less than 9. Enjoy!
Of course you have another 107 jobs in the last two weeks in the board.
If you feel like your skills are not a perfect match yet for those positions check below the jobs, a nice surprise for you.
Bonus: We updated the two internships featured in the website, take a look! They will be pinned until the next update in the following weeks.
Jobs for you:
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One stats guy worth $9 Million
Recently a paper was presented that claims that hiring just ONE additional analytics staffer gives an NBA team as much value as spending $9 million more on player salary.

This is the paper for your reference.
And the main finding is:
“Teams with more analytics staff won more games, even after controlling for several important features”
Which translates to:
How much extra salary would it take to get that same win bump?
The answer is about $9 million.
That’s the value of one mid-level rotation player.
That’s HUGE.
In one hand, I think papers like this one are necessary for the industry to grow, to showcase the true impact of analytics and to measure and be accountable for our work. It’s also really interesting to know how a whole field is performing and, if the results are good, this will trigger more teams to incorporate or expand the analytics department. (good for you and for the sports analytics industry!)
On the other hand, I don’t personally think this is a universal truth. You can read the paper by yourself (or the following thread that summarizes a few aspects). The causality part is not robust and the data itself is mostly a proxy, I don’t think there is enough public data to claim something so powerful with impeccable reasoning but I believe the approach is quite interesting: measuring the impact by extra wins (sounds like Moneyball).
I believe there is value in knowing how to do this and I believe there is value in being transparent and showing the methodology to replicate this with newer data or better data eventually.
And for you, I think it’s useful to get involved in research, to discover sources of data to do analysis and references to a whole set of papers and works where you can deep dive and get lost in the rabbit hole. You will learn a lot, at least by seeing what other people are doing.
What are your thoughts on this? Happy to compare notes!
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