Jason Kroll Email & Phone Number

Greater Seattle Area

AWS DynamoDB Performance

Seattle

We built an excellent Analytics and Machine Learning team.

Greater Seattle Area

Inside Jobs connects careers with education. We use Ruby on Rails, Heroku, PostgreSQL, MongoDB, AWS, and GitHub. After launching the site in my first year, I have done all the dev work for the last 2 years. Here are some highlights:I built a self-generating job sorting and filtering system. Given a seed word like "social", the system churns away on our databases using statistical analysis and natural language processing to assign a "social" score to all jobs. We did this also with "meaningful" and thereby found out what makes a job meaningful (hint: autonomy and social bonds). Currently about 100 filters are live on the site.We developed a system for connecting over 7,000 post-secondary schools in the US to the 15,000+ careers in our system, so that you can find out for any given career what schools in your area can prepare you.We crawled the web for resumes and job listings to identify good stepping-stone jobs to get into a given career and to figure out where one might move up from a given position. Job listings, more so than resumes, help us to identify for different jobs which skills are most in demand by employers.

Greater Seattle Area

iMedExchange was a secure social network for physicians. I came in to replace an entire dev team that was let go, and I quickly turned the site around. We were able to bring in a new team and successfully transition from Ruby on Rails and MySQL to a Java/Spring/Tomcat setup using the graph database Neo4j to provide maximally relevant feeds tailored to each physician.The neatest thing I did was crawl the web to assemble a detailed database of almost every physician in the country. This was a tricky problem because it was full of duplicates and very noisy! But once uploaded into a graph database it actually worked to produce relevant news feeds.

Greater Seattle Area

At ClayValet we built a mixed human and artificial intelligence personal shopping service in Ruby on Rails using natural language processing and Amazon's Mechanical Turk. The system accepted complex natural language queries and returned a detailed report about your purchasing options. I was responsible for the workflow system and the merchant reliability layer.

Greater Seattle Area

I was responsible for verifying the correctness of all technical content in the magazine as well as for performing product reviews. I happened to catch the boom and bust.

I checked technical articles for correctness and style, mostly catching typos and formatting errors with the occasional misconjugation thrown in.

Ms, Computer Science

Activities and Societies: Machine Learning Reading Group Thesis: Computational Applications of Market Mechanisms

Ba, Economics

Activities and Societies: Magic Peace Farm Transition economies, economics of science, history of economic thought