Data Scientist | Python · SQL · Machine Learning · Analytics
I’m a Data Scientist interested in turning complex data into clear insights and practical solutions. My hands-on training includes data analysis, statistical methods, machine learning, time series, and predictive modeling, applied to a variety of real-world business problems.
My background is non-traditional and international, spanning teaching, hospitality, and multilingual work. These experiences have strengthened my adaptability, attention to detail, problem-solving skills, and ability to explain complex ideas clearly to people from different professional and cultural backgrounds.
I enjoy working through messy problems, asking questions, finding patterns, testing ideas, and turning analysis into recommendations that support better decisions. I’m particularly interested in opportunities where data can be used to improve processes, understand behavior, anticipate outcomes, and contribute to meaningful challenges across different industries.
When I’m not working with data, you’ll probably find me marathon-reading romance or fantasy books, teaching English, or spending time outdoors. 🌿
- Programming: Python, SQL, HTML, CSS
- Data Analysis: Pandas, NumPy, SciPy, Data Cleaning, Data Wrangling, EDA, Feature Engineering
- Statistics: Statistical Analysis, Hypothesis Testing, Experimentation
- Machine Learning: Scikit-Learn, XGBoost, Supervised & Unsupervised Learning, Predictive Modeling, Model Evaluation, Time Series
- Visualization: Tableau, Power BI, Matplotlib, Seaborn
- Workflow & Tools: Git, GitHub, Jupyter Notebook, VS Code, CLI
- Cloud: Azure
- Methodology: Agile / Scrum
I build hands-on projects that solve business problems through data, analytics, and machine learning.
📈 Wind Farm Power Output Forecasting Time-series forecasting with XGBoost using historical wind generation data from four German transmission system operators.
🛢️ Oil Well Location Optimization Predictive modeling and bootstrap simulation to evaluate profitability and financial risk across three potential drilling regions.
🎮 Video Game Industry Analysis Exploratory data analysis and statistical testing to identify regional market trends and support marketing and inventory decisions.
📱 Megaline Consumer Behavior & Revenue Analysis Data wrangling, statistical analysis, and customer behavior analysis to identify revenue drivers and plan optimization opportunities.