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Jacob Budnick
Data Scientist Jacob Budnick, Websites, IT & Software
TECHNICAL SKILLS Python: Pandas, NumPy, Matplotlib, SciKit-Learn, SciPy, Tensorflow, Flask Data Science: Data Analytics, Data Visualization, Data Mining, Data Cleaning, Tableau, Statistical Modeling, Hypothesis Testing, A/B Testing, NLP, SQL, PostgreSQL, mySQL, MongoDB Machine Learning: KNN, Logistic/Linear Regression, Random Forest, K-means, RNN/CNN Other: Git/Github, Unix, Docker, Spark, Hadoop, AWS, Matlab/Simulink, MS Office, CAD DATA SCIENCE PROJECTS Colorado Hispanic COVID-19 Susceptibility | Data Scientist | Tableau and Python Collaborated with Halvatzis Consulting and the CO Hispanic Chamber of Commerce to generate a report to illustrate education, environment, and food access factors in highly hispanic regions to provide insight as to why 39% of COVID-19 cases in Colorado have been afflicting hispanics when the overall population is 22% hispanic Utilized census population data, Environmental Protection Agency air quality data, school district graduation rates, and Colorado Department of Public Health and Environment data to explore geospatial trends Cleaned data with Python and presented findings in Tableau plots and maps Found that the hispanic community may be more vulnerable due to poor education, pollution, and low access Forecasting the Future of COVID-19 with Social Distancing | Data Scientist | Python Used New York Times COVID-19 data and mobility statistics from Apple and Google to forecast predictions for the number of new cases for a specific state based on social distancing for states similar in population density Implemented moving averages to smooth out raw data, trained and tested a random forest model to predict future new cases based on time lagged public activity Created a model to forecast new cases and determine feature importances utilizing ScitKit-Learn Quantified level of social distancing to result in decreasing new cases, determined suggestions for 7 states Transition to Renewable Electricity Resources Around the World | Data Scientist | Python Analyzed US Energy Information Administration (EIA) international data to investigate if countries around the world have been producing a greater proportion of electrical energy from renewable resources in 2017 than 1980 Used United Nations Human Development index data to group countries by development level and region Cleaned and analyzed data with Python using Pandas, NumPy, and Matplotlib and presented findings in plots Through hypothesis testing, found that changes in proportions of renewable electricity in the world's most developed countries were not statistically significant to conclude that proportions have been increasing PROFESSIONAL EXPERIENCE Electrical Distribution Systems Engineer April 2018 - January 2020 Product Engineering Designer July 2014 - April 2018 Ford Motor Company | Dearborn, MI Advanced 2021 Ford Mach-E vehicle prototypes through Ford Global Production Development procedure and in new model vehicle production to resolve issues for final vehicle design Led WebEx meetings involving engineers of numerous systems groups and supplier personnel to facilitate resolution of issues in design to release only top quality CATIA data adherent to all Ford CAD standards Design Engineer May 2013 - July 2014 DENSO International America | Southfield, MI Used Lumicam software to measure light intensity and color spectrum backlighting values and analyzed data with Microsoft Excel to ensure customer specifications were met Collaborated with plant team in China to coordinate business requirements for instrument clusters EDUCATION Galvanize, Data Science Immersive Program | Denver, CO June 2020 13-Week program with 700+ hours of coding, team case studies, and capstones Python-based program focused on machine learning, prediction, statistical analysis, and regression Michigan Technological University | Houghton, MI May 2013 BS Mechanical Engineering, Academic Excellence Award Recipient
Websites, IT & Software
Data Visualization
1 $
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