• Performed A/B Testing, Bayesian Statistical Analysis, Linear Regression, Data Analytics, SQL Querying, Image Processing, Network Analysis, and other disciplines.• Constructed a variety of Supervised and Unsupervised machine learning models with 85+% accuracy.• Produced descriptive data visualizations and interpreted findings in documentation and presentations to tell coherent stories to technical and non-technical holders.

• Developed and presented a predictive model using supervised machine learning algorithms to be able to determine if the next pitch any MLB Pitcher throws will be a fastball or an off-speed pitch.• Performed feature and data analysis of pre-pitch categorical and continuous feature variables to determine whether each of these variables are statistically significant to determining whether a pitch is a fastball.• Used GridSearchCV to hyper-parameterize the features of our Classification Models. Resulted in a model accuracy of 66%, which is an improvement of 14% from initial machine learning model’s baseline accuracy of percentage of 52.4%. This increase allows for a greater percentage in home run rates throughout MLB.

• Examined client, Big Mountain Resort, current facility features and compared them to other competitive markets to create a predictive pricing modelto investigate if the company can raise resort prices and by how much to offset additional operating expenses.• Developed baseline performance machine learning model to as a comparator for other subsequent models built. Designed models built to gain insight into what Big Mountain's ideal ticket price could/should be, and how that might change under scenarios.• Successfully found model that would increase revenue by $5.25 million and cut additional operating expenses by $1.54 million.

• Analyzed Walmart sales data to predict department-wide sales for dataset consisting of 45 Walmart retail stores by comparing classic and more common statistical demand forecasting models to the more recent machine learning algorithms to assess if they produce better results.• Hyperparameters used to optimize for our best model showed that Extra Trees Regressor was the best model predictor with R^2 Score of 0.85. Determined that size of store, seasonality, and store department are the biggest contributors to weekly sales by approximately 35%.

• Technical Support Associate intern supporting a team of 20 internal employees including teaching staff, healthcare workers, grant procurement etc; as well as student body. Support tickets received via email, phone and helpdesk system. • Data Entry including updating of, analyzing and maintenance of company data (names, phone, health records, student citizen test exam records) etc via proprietary CRM system and in cataloged archives, which contain over 1000 customer data details, to ensure accuracy across organization. • Devise and review hand –written paper documentation for over 200 students; transpose and transcribe student data information onto fillable electronic form to establish accurate transfer and final review. Consist of conducting profiling and status changes of customer records using company system.• Onboarding, recommending and educating on the various services potential customers can receive including ensuring correct administration to retrieve missing components on service paperwork. • Correspondence with internal and external customers by telephone using an inbound/outbound phone queue and email.

• Basic database administration supporting a team of 20 internal employees including teaching staff, healthcare workers, grant procurement etc; as well as student body.

• Led and mentored students in private, 1:1, sessions in undergraduate and graduate level Math subject areas including but not limited to: Algebra 1, Algebra 2, Calculus 1, Calculus 2, Linear Algebra, and others.• Performed activities like developing tutoring resources, monitoring student progress, and helping with homework and preparing students for tests to obtain desired high scores.• Advised and motivated students during sessions and instituted ability to learn and succeed

• Acted as basic technical support for both internal employees and external personnel by troubleshooting and resolving issues for students.• Assisted in managing technology-related support requests received either by phone, ticketing system, or walk-ins to the Technology Support Desk.• Managed and created support desk tickets and assigned to appropriate departments as needed.• Performed basic maintenance on telecommunications system to troubleshoot system shut downs and increase performance.• Worked with technology support desk supervisor on any tickets/request that required additional assistance.• Referred students, faculty, staff to other departments when needed.• Operated the College’s switchboard and the college's voice messaging system. This system informed over 25,000 personnel of current office hours and any changes to the weekly schedule.