My experience and proficiency with programming languages, linear algebra, algorithms and database concepts is supported by the following facts:
Undergraduate and Graduate School Coursework:
1. In the 3rd semester of my undergraduate program, I had to take a C, C++ programming course and a programming lab. These courses introduced me to both the theoretical and practical applications of the programming languages.
2. I was a math minor at Vanderbilt University and took multiple mathematics courses such as linear optimization, non-linear optimization and error-correcting codes to meet the degree requirements. All these courses required good understanding and application of linear algebra and algorithms concepts. To cite a few examples, in linear optimization course, I learned to solve a system of inequality equations using simplex and revised simplex methods that require matrix computations. Non-linear optimization exposed me to constrained and unconstrained optimization algorithms such as steepest descent, golden section
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My job at Capital One Financial Corporation requires me to have a strong understanding of SQL, SAS, and database concepts. Capital One has several petabytes of data and it is stored in various relational, non-relational (NoSQL) data bases such as Teradata, Oracle, HDFS, mongo DB and SAS data servers. As an analyst, I have to not only understand the underlying data model, table schema and metadata, but also program in SQL, SAS, NoSQL and python scripts to query data from these data structures. While my focus in recent years has shifted to strategic leadership and direction setting, I have continued to demonstrate technical proficiency as an individual performer on various innovation projects. Recently, my team worked on a project to build out metadata wiki pages by leveraging media-wiki APIs. I programmed the prototype using the python APIs and demonstrated the solution to my leadership before handing it off to my team for production