Nathan L Sponberg

440 Millbrae Ave, Millbrae, CA 94030

Internet

Yelp
Senior Data Scientist
Acumen, Llc May 2015 - Aug 2017
Data Analyst and Statistical Programmer
University of Montana Aug 2011 - May 2014
Mathematics Tutor For Trio Student Support Services
Marquette University Jun 2013 - Aug 2013
Undergraduate Researcher In Mathematics

University of Montana 2008 - 2014
Bachelors, Mathematics, Statistics Providence University
Hellgate High School

Stata
Sql
Statistics
Python
R
Sas
Research
Data Analysis
Computer Science
Microsoft Excel
Mathematics
Programming
Technical Writing

English
Mandarin

University of Montana
Missoula, MT
Aug 2013 to Dec 2013
Data Structures Coursework : Data Structures/Algorithms in Python
Marquette University & University of Montana
Milwaukee, WI
Jun 2013 to Dec 2013
MSCS REU (Research Experience for Undergraduates)
University of Montana
Missoula, MT
Jan 2013 to May 2013
Simulations Coursework : Software Development/Modeling in Python
University of Montana
Missoula, MT
Jan 2013 to May 2013
Infosphere Steams Independent-Study Project : Big Data analytics using SPL
University of Montana
Missoula, MT
Jan 2013 to May 2013
Pattern Recognition Coursework : Statistical Programming in R
University of Montana TRiO Student Support Services
Missoula, MT
Aug 2010 to May 2011
Mathematics Tutor
Bernice's Bakery
Missoula, MT
Dec 2007 to Mar 2010
Croissant and bread baker

The University of Montana
Missoula, MT
2014
Bachelor of Arts in Mathematics / Computer Science (Minor)

--Programming knowledge and skills: Experienced in the following programming languages: Python (particularly numpy and scipy), Java, Visual Basic, R, Latex and SPL (IBM's Streams Processing Language). Solid understanding and ability with SQL, Excel and relational databases design. Familiarity with the Eclipse IDE. Extensive experience using both Linux and Windows operating systems as work environments and at home. Proficient in computer data structures, algorithms and object oriented development methodology. --Statistics/Mathematics: Comprehensive knowledge of and facility in mathematical statistics, probability theory, analysis, differential equations, graph theory, abstract algebra and applied mathematical modeling. Well-versed in statistical methodology and theory including: Bayesian inference, confidence intervals, hypothesis testing, bootstrap methods, general linear regression and statistical programming. Also knowledgeable in the area of pattern recognition and machine learning techniques such as clustering, LDA, PCA, and MDS.