I'm in day 1 of my first year at GHC, and holy sh*t (because cow doesn't cut it)! There are thousands of women, representatives from tech giants, academia, and a handful of national labs. The Career Expo is jam packed with so many booths (most have swag) that it's easy to experience some serious sensory overload. There was a LinkedIn booth offering professional head shots! Tech demos and representatives all wanting a copy of your resume and wanting to talk to YOU about your career interests and where you could see yourself in their company. If this isn't incentive to retain women in tech, then I don't know what is.
I applied for an AnitaB.org scholarship to attend the Grace Hopper Celebration, and they covered my flight, hotel, registration, and a $450 card to cover food, travel expenses, and anything else I may need. Feeling pretty good to be a Scholar! I was able to reconnect with peers from a reception held by CRA-W and and visit representatives from ACM-W. I'm a member of both, and you can never pass up an opportunity to network! It was good to see people I met at the CRA-W Grad Workshop last spring.
AnitaB sets you up with a roommate, and I lucked out and got someone who's pretty down-to-earth and nice all around. She's an undergrad at Pace and it sounds like her interviews are going off with a bang (she's already got an internship offer). It's mind-boggling how many opportunities this conference offers to women who are at any point in their career. The support and effort from the tech community is warranted - I mean, when women only represent approximately a fifth of tech companies on average (and the US population is approximately 50/50), you're missing out on a huge chunk of talented workforce. As a technologist you can make a fairly decent salary and have the ability to do work that has impact. We just need things like GHC to remind women that there is light at the end of the rainbow ... oops, tunnel.
Through my data wrangling career, I never had a label I could use that would convey to someone what it is that I do. It wasn't until the last couple of years that I realized it might be data science. If someone told me before this year that I was a data scientist, I probably would have told them they were mistaken.
All of the workshops I signed up for are for data science or artificial intelligence. It was through the two data science workshops today that I realized that I truly am specialized in this field. I mean, if all of it seems like 'common sense' (when it really isn't), then it probably means that this is the label I was looking for all along. If it looks like a dog, barks like a dog, and smells like a dog ... it must be a dog, right?
I have this issue with labels. I don't want to apply them to myself unless I'm absolutely certain I meet all of the qualifications for that label. Due to this, I am incredibly reluctant to think I am anything, so I give very general information to people about what I do. To which they usually politely nod and smile, with eyes slowly drifting over my head and gazing into the distance. Now that I say, "it's basically data science, but with a focus in spatial data" their eyes dart back and they get these knowing smiles on their faces. Data science seems to have rapidly become this "it" field, which seems weird, because I feel like I've been doing "it" for more than a few years with polite [dis]interest from outside observers. It is nice to have some recognition though, and have people say, "hey, that's useful research!". Recognition is a motivator because it tells you in some way that your research is valid. For obvious reasons, you shouldn't need it, but it certainly feels good sometimes!