Evident Skills

 
Ghosting is a term taken from the world of dating in the digital age - it's basically when you meet somebody and things go seemingly okay, but then you never hear from them again; no returned messages, nothing.
It's a terrible feeling after having what you thought was an awesome conversation with a recruiter at an awesome company. And if it happens to you, it might be a good idea to self reflect rather than blame the recruiter for being a jerk - I suppose that's the natural gut reaction many people have to being ignored. Been there, done that. Combining this feeling with research on why recruiters ghost in the first place, you might realize that you are hurting yourself in terms of how you are marketing yourself on LinkedIn and in your CV.
Just because you did a tutorial, read a book, or took a MOOC doesn't mean you have the right to list that skill on your CV. What did you make with it? 
If you simply list a bunch a keyword skills without having evidence - open source repositories or commercial products - of your ability to use those skills, then the chances of you getting "ghosted" by a recruiter after that first interview increase dramatically. So why do they do it? I am guessing there are two reasons: 1) They are too busy to deal with you, the reason for which is 2) they are being polite - WHAT?
Isn't it more polite to ignore you rather than tell you to your face that you are misrepresenting your skills - essentially saying you suck!
Addressing my most recent experience at Translational. What have I actually done? I have been working with a 38Gb dataset for validation of a specific machine learning methodology using Support Vector Machines, Naive Bayes, Linear Discriminant Analysis, and k-Nearest Neighbors, as well as filter and wrapper models to reduce dataset dimensionality - all based on the work of previous researchers. Further, I have then used this dimensionality reduction scheme to then create predictive classification models using SVMs. Ultimately, the end goal of this project is to apply these methodologies to an even larger dataset (30+ terabytes) with the intention in future of using Deep Neural Nets to increase accuracy and see if there is anything unexpected in the data.

So what useful skills does this experience relate to a potential future employer? Big data - 38Gb is not big data in 2018, but 30 terabytes certainly is. How about Machine Learning Algorithms - yeah, I got several of those in there. What programming languages have I been using? Python and GNU Octave - both with editors/command line interfaces and Jupyter Notebooks (might be a few more skills in that line as well). What Operating Systems have I been using? Linux and MacOS. Have I used any databasing technologies on this project? Other than Pandas? Not so far. What else? I would probably say Research and Research Reproduction, maybe Validation Studies, and Confidence Intervals.

I could probably list more, but lets move on to my next experience at New Oriental Education & Technology Inc (XDF) based out of Beijing, China. I started at XDF as an English teacher after my wife and I closed the retail stores we had been running for five years in Hohhot, China. I was a good teacher and I enjoyed using my own interactive websites to help keep my students informed, motivated, and engaged. Only later on was I brought on as a linguistic consultant - a fancy way of saying I was an output sanity checker - for their RealSkill system. RealSkill is a service based on natural language processing technologies that allows Chinese students of the English language to get an automatic score of their practice IELTS English proficiency tests. It's a cool product and I'm proud to have helped in my small way, but what skills does this experience give me the right to put on my CV? Teaching - sure, but not really related to my career goals. Web Development - yeah, but how awesome is coding in HTMLCSS, and JavaScript at such a basic level for data science and machine learning roles? Not so much. Natural Language Processing - haha, nah, I was on the outside looking in on this aspect of the experience, so how about let's not put that on my CV. Still, good to mention that this was the first experience that motivated me to want to study machine learning.

Again, I could list more here for both these experiences - and I have on my LinkedIn profile and CV - but that is besides the point. The problem lies with what additional skills I listed.
I did a tutorial, read a lot of books, and took a lot of MOOCs and then put those skills on both my profile and my CV. But, I didn't make anything with them.
Now, these are all wonderful ways to build skills in Computer Science - and employers and recruiters like to see them as they show a hungry, curious mind that is eager to learn new things. But you have to do or build something with them - you have to have evidence. I have been absorbing these materials like an addict for several years now and I REALLY want to show off to potential future employers that I know what these are and I know how to do them. But do I really know how to do them? What have I made with them?

This is the fundamental question you have to ask yourself before you put a skill on your profile or CV. What have you made with this skill? If the answer is "nothing, yet" then leave it off. Good recruiters will figure it out in the first interview, and bad recruiters will figure it out when the technical team lead scolds them for wasting his or her time. A good way to get ghosted, either way.

So do this. Have an honest assessment of your skills. Figure out which ones you've actually used to build something, and list only those. Then go build something with the tools and skills that you really WANT to put on your profile. This is what I'm going to do moving forward.

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