Business Management Professional | Marketing Analytics | Data Strategy
Transforming complex datasets into actionable business growth and strategic ROI.
| Category | Tools & Technologies |
|---|---|
| Data Science |    |
| Databases |   |
| BI & Viz |   |
- Business Problem: How to optimize marketing spend in a 400k+ transaction dataset?
- Solution: Developed an RFM model in Python to identify high-value "Champions" and "At-Risk" segments.
- Result: Provided actionable insights for a 20% targeted retention campaign.
- Tech:
Python,Pandas,Matplotlib,Marketing Analytics.
- Business Problem: Minimize financial loss from loan defaults in a high-risk portfolio.
- Solution: Built a Logistic Regression model with
Scikit-Learn, optimizing for Recall to detect potential defaulters. - Result: Increased detection of toxic loans from 27% to 71%, potentially saving millions in bad debt.
- Tech:
Python,Machine Learning,Risk Management Strategy.
Description: Analyzed 8,000+ digital marketing campaign records to audit ad spend efficiency, maximize Return on Investment (ROI), and identify high-converting customer acquisition channels. Tools: Tableau, Data Analysis, Business Intelligence, Logical Modeling, Financial KPIs. Key Achievements:
- Engineered core financial KPIs (Net Profit, ROI) using calculated fields to translate raw transactional data into actionable business metrics.
- Identified the Referral channel as the primary revenue driver, generating $14.1M in net profit and outperforming paid channels with a 162.9% average ROI.
- Formulated a data-driven strategy to reallocate 15% of underperforming social media ad budgets toward scaling high-yield customer loyalty programs.
| Status | Primary Focus | Main Goal |
|---|---|---|
| Active | Customer Intelligence | Driving ROI through Data |
