Backend engineer at Bleacher Report, primarily supporting the data science team in doing data engineering, data warehousing, and model APIs.

Developed a highly accurate, user preference-tailored movie recommendation system for rottentomatoes.com using Hadoop and Mahout with the well-known ALS-WR algorithm running on Amazon EMR. Data size was extremely large, reaching into the billions of user ratings.

Developed a new method for measuring movie similarity, which could be leveraged for more targeted advertising as well as gaining better understanding of the user base.

Developed a client-side image cropping and processing widget in order to improve performance with images. Used the Zend Framework and the Smarty template engine for back-end organization. Employed memcached to improve page load times and to relieve database stress. Performed Quality Assurance and debugging duties.