Skills & Technologies
Technical Skills & Expertise
My technical toolkit spans programming languages, statistical software, and specialized libraries for economics, machine learning, and data science applications.
Programming Languages
Python
Advanced Proficiency - Primary language for research and development
I have extensive experience with Python across multiple domains, from academic research to practical applications. My Python work demonstrates proficiency in:
- Advanced data analysis and statistical modeling
- Machine learning and deep learning implementations
- Real-time data processing and API integration
- Research-grade code with reproducible results
R
Advanced Proficiency - Statistical analysis and econometric modeling
Deep expertise in R for economic research and statistical analysis:
- Econometric modeling and time series analysis
- Advanced statistical methods and hypothesis testing
- Data visualization and reporting
- Academic research and publication-quality analysis
Stata
Proficient - Econometric analysis and research replication
Solid foundation in Stata for:
- Applied econometric analysis
- Research replication and robustness checks
- Academic research standards
- Policy evaluation and causal inference
LaTeX
Proficient - Academic writing and document preparation
Experience with LaTeX for:
- Academic paper preparation
- Research documentation
- Professional presentations
- Mathematical notation and formatting
SQL
Intermediate - Database management and data extraction
Working knowledge of SQL for:
- Database querying and data extraction
- Data pipeline development
- Business intelligence applications
Python Libraries & Frameworks
Machine Learning & Deep Learning
TensorFlow & Keras
- Neural network architectures for time series and NLP
- Real-time prediction systems
- Advanced model optimization and tuning
PyTorch
- Deep learning research and experimentation
- Custom model development
- GPU-accelerated computing
scikit-learn
- Classical machine learning algorithms
- Model evaluation and cross-validation
- Feature engineering and selection
LightGBM
- Gradient boosting for structured data
- High-performance predictive modeling
- Ensemble method implementations
statsmodels
- Statistical modeling and econometrics
- Time series analysis and forecasting
- Hypothesis testing and inference
Natural Language Processing
Transformers & Hugging Face
- State-of-the-art language models
- Text classification and sentiment analysis
- Custom NLP pipeline development
sentence-transformers
- Semantic text embeddings
- Document similarity and clustering
- Information retrieval applications
Advanced Text Processing
- tiktoken, tokenizers for text preprocessing
- Large-scale text analysis
- Real-time text processing pipelines
Data Analysis & Visualization
pandas
- Advanced data manipulation and analysis
- Time series data processing
- Large dataset handling and optimization
NumPy
- Numerical computing and linear algebra
- Array operations and mathematical functions
- Performance optimization
polars
- High-performance data processing
- Modern DataFrame operations
- Memory-efficient data analysis
matplotlib & seaborn
- Statistical data visualization
- Publication-quality figures
- Interactive plotting and dashboards
Specialized Libraries
Financial & Economic Data
- Real-time financial data processing
- Economic time series analysis
- Market data integration and analysis
Research & Academic Tools
- Jupyter ecosystem for research notebooks
- Academic-standard documentation
- Reproducible research workflows
Research & Analytical Skills
Econometric Methods
- Causal Inference: Difference-in-differences, instrumental variables
- Time Series: ARIMA, VAR models, cointegration analysis
- Cross-sectional: Regression analysis, matching methods
- Panel Data: Fixed/random effects, dynamic panel models
Machine Learning Applications
- Predictive Modeling: Classification, regression, forecasting
- Feature Engineering: Domain-specific feature creation
- Model Evaluation: Cross-validation, performance metrics
- Ensemble Methods: Model combination and optimization
Data Science Workflows
- Data Pipeline Development: ETL processes, automation
- Real-time Processing: Streaming data and live analysis
- Business Intelligence: Dashboard creation, reporting
- Research Infrastructure: Reproducible analysis frameworks
Domain Expertise
Financial Markets
- Stock price prediction and analysis
- Real-time sentiment analysis for trading
- Risk modeling and portfolio optimization
- Market microstructure analysis
Applied Economics
- Labor market analysis and policy evaluation
- Development economics and growth modeling
- Health economics and impact assessment
- Public policy analysis and causal inference
Data Science Applications
- Large-scale text processing and NLP
- Business intelligence and analytics
- Predictive modeling for decision support
- Research tool development
Software Development Practices
Version Control & Collaboration
- Git/GitHub for code management
- Open-source project contribution
- Collaborative research workflows
- Code review and documentation standards
Research Standards
- Reproducible research practices
- Academic-quality code documentation
- Statistical software best practices
- Data management and archiving
Performance Optimization
- GPU computing for deep learning
- Memory-efficient data processing
- Parallel computing and optimization
- Scalable algorithm implementation
Continuous Learning
I stay current with developments in:
- Econometric Methods: New causal inference techniques
- Machine Learning: Latest architectures and approaches
- Data Science Tools: Emerging libraries and frameworks
- Research Methods: Best practices in reproducible research
My technical skills continue to evolve through active research, practical applications, and engagement with the broader academic and professional community.