I am a data scientist with a PhD in Economics — passionate about using data science, analytics, and economic reasoning to solve business, technology, policy, and finance problems.

I specialize in:

• Predictive Modeling - Building models to forecast trends and outcomes
• Causal Inference - Identifying cause-and-effect relationships in complex systems
• Regression Analysis - Uncovering relationships between variables
• Data Visualization - Transforming complex data into clear, compelling insights
• Impact Evaluation - Measuring the effectiveness of programs and policies

• Providing data science and economic consulting services
• Developing expertise in deep learning and Artificial Intelligence

Fast Fraud Screening Using Lightweight Models
Developed an efficient fraud detection system using lightweight machine learning models to flag high-risk transactions before deep analysis. Implemented predictive models that balance accuracy with computational efficiency, enabling real-time risk assessment.

Government Financial Inclusion Policy an Impact Evaluation
Using a difference-in-differences methodology I examine the impact of the government lead financial inclusion strategy.

Programming Languages:
Python • R • STATA • SQL

Data Analysis & ML:
Pandas • NumPy • Scikit-Learn • XGBoost • PyTorch • Tidyverse • Tidymodels

Visualization:
Tableau • Matplotlib • Seaborn • ggplot2

Other Tools:
Git • Jupyter • R Markdown •LaTeX

💡 Open to collaborations in data science, economic research, and impact evaluation projects!