Amarita Natt, PhD

An economist who loves data modeling and coffee!

[Amarita Natt, PhD @econamar]

@lucas_a_meyer Another parent at my son's school admitted that she put Air Tags on both her kids when they went to Disneyland recently. Our generation's child leashes...

[Amarita Natt, PhD @econamar]

@lucas_a_meyer It's the little things, really.

[Amarita Natt, PhD @econamar]

@lucas_a_meyer Analyst to me: why won't the model converge?? It's been running for ten hours!
Me: Who understands the whims of the modelling gods? Also, you probably should have run it on the server instead of your laptop.

[Amarita Natt, PhD @econamar]

@kdpsinghlab That's how I felt during the pandemic when every company felt compelled to tell me how they were taking precautions. Like, whoa, I forgot this store even existed.

[Amarita Natt, PhD @econamar]

Remember: it's really easy for AI/ML to perpetuate bias in hiring (and all sorts of other things) simply by functioning as designed and training on biased data being produced by inherently flawed systems already in place.
https://t.co/G0BMU3Vq7l

[Amarita Natt, PhD @econamar]

@kccarrell Oh, I've absolutely done that, except I went to rant to a co-worker about it and they pointed out that it was my own work product. Then they laughed at me. A lot.

[Amarita Natt, PhD @econamar]

Accurate.

[Dr Kareem Carr @kareem_carr]

* Python vs R in one tweet *
graphics: R
ease of use: R
speed: Python
diversity & inclusiveness: R
machine learning: Python
statistics: R
unstructured data: Python
structured data: R
big data: Python
app development: Python
software engineering: Python
employability: Python

[Amarita Natt, PhD @econamar]

@RandiRLudwig Okay I need you to tweet every conference and also I'm jealous you got to go to this talk!

[Amarita Natt, PhD @econamar]

I did a thing! @AnnaOnTheWeb and I had a great convo about that inevitable c-suite question: What can we do with our data? Take a look!
#womenindata #datascience #econladies #consulting

[AI♥️Data @AILovesData]

On this week's #DSSBreak @AnnaOnTheWeb sits down with @econamar, Managing Director, #DataScience at Econ One Research, where she creates #predictivemodels using client data to optimize business outcomes. Be sure to 'like' & subscribe to our channel!

https://t.co/1X6YAUx7tw

[Amarita Natt, PhD @econamar]

I often discuss the question of "we can, but should we?" in data science. This is a perfect example of no, we should not.
https://t.co/btTcoJADzu

[Amarita Natt, PhD @econamar]

After a ridiculously long hiatus from twitter, I tried to log on and...forgot my password. That, of course, made me wonder if I should just extend my hiatus :P

[Amarita Natt, PhD @econamar]

@dikayodata @business Aww thank you!!! I loved doing the podcast with you. I'm trying to think about podcasts and conferences to speak at this year...any thoughts?

[Amarita Natt, PhD @econamar]

@siawayforward true story.

[Amarita Natt, PhD @econamar]

@shunley42 It can be both...

[Amarita Natt, PhD @econamar]

I've been honored to do work with Sixto and Think of Us, analyzing some of their data from foster youth and kinship caregivers on their needs and experiences.
https://t.co/1IbdqSaVhg

[AI♥️Data @AILovesData]

@econamar, Sr. Economist at Econ One Research shared her thoughts on the latest #DSSeroundtable with "Why we need more women in data science now". Now on the blog 💭

https://t.co/bM27XI5EHM

#datasciencewomen #womenindatascience #datasciencecommunity

[Amarita Natt, PhD @econamar]

@sirinyamatute @jasonislas @MsCapoot And once again I'll just coast on the back of your good parenting...

[Amarita Natt, PhD @econamar]

@kccarrell This is such useful and actionable insight.

[Amarita Natt, PhD @econamar]

@SchaferEcon Great blog, Leslie!

[Amarita Natt, PhD @econamar]

I needed this today! Maybe you do too. Thanks, @SchaferEcon!

[Danielle C. Belton @daniellecbelton]

Erykah Badu once said, "I'm an artist and I'm sensitive about my shit" which is something I very much was about when I first started out as a writer, but now, 10,000 years and as many cuts later, it's more like "You can't kill what's already dead inside."