Another win by Gennady Korotkevich! Congratulations! I've always wondered how this level of skill must translate into being a software engineer or ML engineer. There's no doubt all of these contestants have a great level of mathematical maturity. Anyone ever worked with an engineer that does these? I'd be interested in your perspective.
Thanks for sharing! I am actually looking for a machine learning based app that can parse resume and job postings and predict a set of relevant and meaningful interview questions that the potential employer may ask during the interview. It would be better if it's for finance/accounting career category.
Job descriptions on advertisements (i.e. not the internal description, which is probably confidential as it depends on internal goals which are not published or yet met) are likely very generic copy-paste for something close to the mark, or an aspiration this is the company we are (but aren't... yet).
Especially in finance, where publishing anything has the chance to rock the boat in a highly regulated industry with a conservative culture cascaded down.
The apps headhunters use in this industry simply match keywords and regularly occurring phrases between CVs and JDs, and are highly ineffective. If you're looking to target 'fit' it might be a good to look at culture in specific institutions crossed with role type (i.e. Ops, Dev, Coverage, etc). That might yield something interesting. Good luck!
For the past year, since graduating in May 2015, I've worked as a mostly-backend software developer in the Java domain. I recently took it upon myself to move to San Francisco to be a part of the excellent tech culture this place is known for. At my last job I contributed a handful of features that used directed graphs, depth first search, and memoization at their core. I'm a passionate programmer and quick learner.
I can only speak for myself but I'm at my first job out of university -- been here about 11 months -- and 6 months in I was tasked with implementing a feature that required directed graphs, (recursive) depth first search, and memoization at its core. These weren't concepts I was told to use ahead of time but ended up coming in handy to conceptualize the problem in the most basic way, without letting business rules cloud my thought. I don't have a degree from a top 100 school or work at an exotic place either, and I don't think my situation is unique. Just wanted to add a counter example.
>Using a set of open source machine learning algorithms known as SciKit Learn—code freely available to the world at large—the service seeks to automatically identify blatant vandalism and separate it from well-intentioned changes.
It's a Python library, available for free download [1]. I've got a book or two on it I've been meaning to read.
Hey if you're looking for a community that will encourage you while working through SICP, drop by #symbolics on Freenode. A few of us are working through the book, including myself, and many have worked through most of it before.
I’m trying to work through the book as well! I’ve found a great IRC community over on the Freenode server. The channel is #symbo1ics. It’s been a sweet place for motivation so far. I’m sure you would be welcomed with open arms! Good luck, and hope to see you there!
Remote: Yes
Willing to relocate: Yes
Technologies: Javascript (ES6), Polymer, React, Underscore, JQuery, Python
Resume: https://www.linkedin.com/in/miles-stevenson
email: miles.d.stevenson@gmail.com