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Data Computer Science

Location:
Chicago, Illinois, United States
Posted:
January 08, 2017

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JAMES MWAKICHAKO

acx557@r.postjobfree.com +*********22 2932 South Wentworth Ave, Chicago IL 60616

https://www.linkedin.com/in/jamesmwakichako

github.com/jmwaks

EDUCATION

Illinois Institute of Technology

Msc Data Science 2017

Bsc Applied Mathematics 2016

Minor Computer Science

Graduate Coursework : Machine Learning, Bayesian Computational Statistics, Advanced Database Organization, Data Mining, Mathematical Modeling, Regression and Forecasting

Undergraduate Coursework: Statistics, Data Structures and Algorithms, Probability, Information Retrieval, Linear Algebra, Object-oriented Programming and Design, Linear Optimization

PROGRAMMING SKILLS

PROFICIENT: Java, Python, SQL, REST, Postgres

FAMILIAR: C, Clojure, C#, Matlab, Mathematica

WORK EXPERIENCE

HERE Maps, Automation Engineering Intern, Chicago, IL May 2016 Current

• Increased test coverage of smoke and regression tests from 6% to 25% in 3 months using Python (pytest framework)

• Running automatic and manual smoke and regression tests and reporting results to appropriate stakeholders.

• Working with stakeholders to come up, design and implement integration tests to enhance code quality

Chicago Bridge and Iron (CB&I), Software Engineering Intern, Plain ield, IL May 2014 Aug 2014, Jun 2015 Aug 2015

• Developed an engineering application in Mathematica used in the process of designing composite elevated tanks..

• Designed and developed a user friendly Graphical User Interface (GUI) in Java

• Facilitated the migration of legacy code from Fortran to Java

• All code was reviewed, perfected, and pushed to production.

PROJECTS

NBA MODELING PROJECT, ILLINOIS INSTITUTE OF TECHNOLOGY Jan 2016 Jun 2016

• Developed a logistic regression model using R aimed at predicting the number of wins an NBA team would have in a regular season. Model had 77% prediction accuracy

• Collected and cleaned up raw data on NBA teams from 1979-1980 to 2013-2014 seasons

• Performed variable selection to find the best model. Used backward elimination, forward selection and stepwise regression

• Ran a k-fold cross validation to ascertain the validity of the model

HUMANITIES DEPARTMENT DATA ANALYSIS PROJECT Sep 2015 Dec 2015

• Worked with Professor Lulu Kang to find out if the current standards used to place incoming freshmen in certain classes is credible

• Preprocessed 1508 data records of freshmen admitted in the humanities department over the past four years

• Created and analyzed multiple linear regression and generalized linear models using R

AWARDS

Illinois Tech Leadership Academy Scholar, Illinois Tech Sep 2014 Clinton E. Stryker Distinguished Service Award, Illinois Tech Apr 2015

ACTIVITIES

Society of Industrial and Applied Mathematics (SIAM) Jan 2013 Current Association for Computing Machinery (ACM) Jan 2016 Current The Collegiate Entrepreneurs’ Organization (CEO) Sep 2016 Current National Society of Black Engineers (NSBE) Jan 2014 Current



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