About Michael Woytek
Background
I'm a detail-oriented senior data analyst with several years of experience working with larger datasets. I have also worked on many machine learning projects using ensemble regressors, support vector machines, K-nearest neighbors, and many other techniques.
Skills
I have proven experience using SQL, Python, Microsoft Excel, Tableau, and Microsoft Power BI for data analysis and machine learning. At, Numerator, I use SQL to manage a database with 10M+ records updated daily.
Education
I graduated from Bowling Green State University with a Bachelor of Science in Business Administration specializing in economics and business analytics with a minor in history.
My Resume
Career History
Senior Data Analyst, Numerator
April 2023 – Present
- Designed custom multivariate product analysis reports for clients, enabling targeted market strategies.
- Automated data cleaning and database management with SQL
- Collaborated with the sales team on client requests and marketing presentations for clients.
Data Volunteer, Political Campaign
August 2024 – November 2024
- Designed and analyzed voter sentiment surveys to refine campaign messaging.
- Hosted and organized phone banks and community events to boost voter engagement.
- Provided technical support to volunteers, ensuring smooth operation of campaign tools and events.
Data Analyst, Numerator
July 2020 – April 2023
- Used SQL and Python to manage, clean, and maintain a database of 10M+ records for Fortune 500 clients.
- Collaborated on transcription machine learning models, contributing to improved accuracy and scalability.
- Conducted routine pricing and sales studies on products in the consumer goods sector.
Education
Bowling Green State University (BGSU), Bowling Green, OH
Bachelor of Science in Business Administration
Specializations: Economics & Business Analytics
Minor: History
Graduated: May 2019
Formal training on Tableau, Microsoft SQL Server, Microsoft Excel, R, and model building with machine learning.
Machine Learning Projects
Interactive COVID-19 Impact Dashboard – Used SQL (including aggregations, CTEs, and views), Excel, and Tableau to identify and visualize countries most affected by the pandemic, both per capita and in total cases, enabling clear data-driven insights for trend analysis.
College Ranking Analysis – Used Python and SQL to analyze the characteristics of colleges to predict their ranking and alumni salary using KNN, OLS regressions, random forest regressors, and more.
2019 Index of Economic Freedom – Used data cleaning and machine learning techniques in Python to visualize trends of countries contained in index. Analysis includes several regressions, principal component analysis, and linear discriminant analysis.
Banco de Portugal Marketing Data – Used Python to analyze the customer characteristics in this data set. Included use of ANOVA, K-nearest neighbors, classification trees, logistical regressions, and other statistical techniques.
Spotify Song Popularity Analysis – Used SQL, Python, and Tableau to perform predictive modeling on a song’s popularity based off of several metrics through a random forest ensemble regressor
2017 Internet Usage Analysis – Used Microsoft Power BI to compare several economics and developmental metrics to build a model for predicting a country's internet usage rate.
Annual Convenience Store Transaction Analysis – Used Tableau to analyze the transaction data for a convenience store over a given fiscal year. This includes time-series analysis and forecasting.
IMDb Movie Rating Analysis – Applied PCA, regression analysis, KNN, and SVM in Python to identify predictors of movie ratings. Cleaned and processed raw data and visualized insights using Matplotlib and Seaborn to support model interpretation.
Activities
President of Analytics, American Marketing Association
March 2016 – August 2018
- Collaborated on marketing case competitions for eBay and Mary Kay.
- Implemented new systems for collecting data, increasing information from members by 50%.
President, Economics Club
August 2017 – May 2018
- Increased club membership 166% by implementing larger marketing campaigns and featuring club in university events.
- Constructed Excel database to maintain club financial and membership information.
Honors
Cum Laude – Graduated BGSU with academic distinction, May 2019
Alumni/Faculty Economics Scholarship – BGSU, February 2018
Skills
Data Management: Microsoft SQL Server, MySQL
Visualization: Tableau, Power BI
Machine Learning: Regression, Random Forest, SVM, KNN, PCA, A/B testing
Contact Me
Questions or Comments
Send me a message or ask me a question using this form. I will do my best to get back to you soon!
My Contact Information
Phone: (440)289-3027 Email: woytekm22@outlook.com
This website uses cookies.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.