Forthcoming M.S. computer science candidate specializing in computational operations research looking to begin a career (Jan 1 2013) in large scale data analytics that utilize high performance computing techniques. Profiled, analyzed and implemented ground data processing algorithms for cluster computing environment at the National Aeronautics and Space Administration (NASA). Assisted the development of job scheduler using PostgreSQL, PERL, and object-oriented programming. Researched and proposed distributed cluster computing for micro satellites in highly constrained project environment. Architected personal cluster to assist research and projects in machine learning, data mining, and natural language processing.
1. M.S. in Computer Science - College of William & Mary (Dec. 2012).
- Specializing in Computational Operations Research
2. B.S. in Applied Mathematics - Baylor University (May 2011).
What important truth do very few people agree with you on?
For folks who desire to have fun playing with data and develop both strong technical ability and skills to apply data science and analytic results to critical business issues.
A data scientist is somebody who can play with data, spot trends and learn truths few others know. Data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes.
Data Science: the analysis of data creation. The data scientist has a solid foundation in computer science, modeling, statistics, analytics, math and strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.
Business Analytics: the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis.