- Spearheaded the development of an advanced algorithm in collaboration with LabelMaster to maximize revenue and enhance conversion value in Google Ads expenditure.
- Utilized various techniques such as exploratory data analysis, data cleaning, outlier analysis, feature engineering, and model selection to build the algorithm.
- Implemented random forest regression and linear programming with PuLP to automate the prediction of optimal bid values for search keywords in the Google Ads platform, resulting in efficient ad spend optimization.
- Achieved an impressive 15% increase in lead conversions while effectively reducing costs by leveraging Power BI dashboards for exploratory data analysis and visualization of Google Ads data.
Please note that the code and data related to this project are not publicly available as I have signed a non-disclosure agreement with LabelMaster.
Analytical Skills, Optimization, Feature Engineering, Data Modeling, Exploratory Data Analysis, Model Development, Statistical Data Analysis, Microsoft Power BI, Microsoft Excel