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Myles Baker
  • Williamsburg, VA
  • United States
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Profile Information

Short Bio:
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).
My Website or LinkedIn Profile (URL):
Field of Expertise:
Business Analytics, Data Mining, Marketing Databases, Operations Research, Statistical Programming, Statistical Consulting, Environmental Statistics
Years of Experience in Analytical Role:
Professional Status:
Student, Technical
Finding a New Position, Networking
What is your Favorite Data Mining or Analytical Website?
What Other Analytical Website do you Recommend?
Your Company:
National Aeronautics and Space Administration, United States Government
Space Technology

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At 10:16am on August 13, 2012, Michael Walker said…

New Meetup Group: Data Science & Business Analytics

Please join us @

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.


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