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Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in analytics.
- Microsoft Office
- R Studio
- Visual Studio
Developed and lead Arduino projects based on C++.
Lectured on C++ to approximately 200 students.
Assisted faculty with in-depth data research in both lab and office environments.
Used Excel to enter data into project database and provided updates on weekly basis.
Validated incoming data to check information accuracy and integrity while independently locating and correcting concerns.
Lead Data Analyst, Web Developer, and Communications Liaison
Analyzed demographics of students at Dearborn and keynote speakers to optimize UI.
Tested websites and performed troubleshooting prior to deployment.
Data Analyst and Business Intern
Analyzed different aspects in Blockchain to incorporate parking availability for the citizens of Detroit.
Planned and conceived computer systems using information engineering, data modeling and structured analysis.
Expedited industry-wide recognition, company awareness, and valuable insights for Detroit
Researched new technologies, software packages and hardware products for use in website projects.
Applied knowledge of data modeling and statistical analysis to note trends and draw conclusions.
Member of SWE
Dean’s List Winter and Fall 2019
Coursework in Computational Analytics, Data Analytics/Management and Algorithms and Design
Mass Shootings Model
- Formulated data regression analysis of the relationships between 5 factors of the offender and 60 years of mass shooting data
- Analyzed complex data sets using R and RStudio to identify errors and remove outliers in data
- Developed a confidence bootstrapping model to forecast most unsafe cities for specific genders, mental health, motives, ages, and the year
- Researched various systems to maximize prevention of mass shootings for populated cities
STEM Research Model
- Created multiple regression models using Tableau and Minitab to analyze the correlation and trends between STEM, race, gender, and student demographics across the U.S.
- Identified STEM majors with the largest growth of female students and workers
- Discovered that states with a higher number of businesses and incomes increases number of women earning STEM degrees
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