I’m writing this README to give whoever is reading it a little bit of backstory.

I recently completed my Master's in Agricultural Engineering (Agroecology), a field focused on building more sustainable agricultural systems. It might not seem like the obvious path into data analytics, but that's exactly where my journey started.

During my master's, I took a Crop Modeling course where I was introduced to programming, simulations, and data-driven decision making. Later, my thesis involved working with millions of data points, building predictive models, analyzing climate scenarios, and creating large visualizations. Somewhere along the way, I realized something unexpected, I genuinely enjoyed writing code more than writing papers.

What started as a tool for research quickly became a passion.

The more I learned about data analysis, machine learning, and visualization, the more I wanted to explore. That curiosity eventually led me to complete the Hamrah Aval Data Analysis Bootcamp, where I worked on a diverse collection of end-to-end projects covering SQL, Power BI, machine learning, statistics, forecasting, and data visualization.

Today, I specialize in transforming complex datasets into actionable insights through business intelligence, predictive modeling, SQL analytics, and data visualization. I enjoy working across the entire analytics workflow, from data preparation and modeling to building interactive dashboards and communicating results that support better decision-making.

My GitHub is a collection of projects that reflect different aspects of the data analytics workflow, from data preparation and statistical analysis to business intelligence dashboards and machine learning models.

• Interactive Power BI Dashboards
• Data Modeling
• DAX
• Power Query
• KPI Development
• Dashboard Design

• Complex Joins
• Common Table Expressions (CTEs)
• Window Functions
• Subqueries
• Analytical Reporting
• Query Optimization

• Classification
• Regression
• Feature Engineering
• Model Evaluation
• Hyperparameter Tuning
• Scikit-learn

• Prophet
• SARIMA
• Forecast Evaluation
• Time Series Preprocessing
• Feature Engineering

• Business Storytelling
• Matplotlib
• Seaborn
• Analytical Reporting
• Tableau

A large-scale machine learning project for predicting building energy consumption using extensive feature engineering, weather data alignment, and gradient boosting models including XGBoost, LightGBM, CatBoost, and Random Forest.

Designed an end-to-end business intelligence solution featuring a star schema, Power Query transformations, DAX measures, applicant risk analysis, drillthrough pages, custom tooltips, and executive KPIs.

Built and compared Prophet and SARIMA forecasting models to predict household electricity consumption, and evaluated their performance using multiple forecasting metrics.

Developed and compared Decision Tree and Support Vector Machine models for insurance claim prediction, including data preprocessing, feature engineering, and hyperparameter tuning with GridSearchCV.

Created an interactive dashboard analyzing vehicle pricing, brand performance, market distribution, and automotive trends using Power BI.

Answered analytical questions using SQL through CTEs, window functions, subqueries, ranking, and comparative performance analysis on FIFA World Cup data.

• Python
• SQL
• R

• Pandas
• NumPy
• Scikit-learn
• Statsmodels
• Prophet
• XGBoost
• LightGBM
• CatBoost

• Power BI
• DAX
• Power Query
• Tableau
• Grafana

• SQL Server
• Prometheus

• Git
• GitHub
• Jupyter Notebook
• Google Colab
• Microsoft Excel

One of the things I enjoy most about data analytics is that every project starts with a different question. Sometimes it's predicting future energy consumption, sometimes it's building a dashboard for business decision-makers, and sometimes it's uncovering patterns hidden inside a dataset with SQL.

That's what keeps this field exciting for me. There's always a new problem to solve and a better way to tell the story behind the data.

📧 Email: torkanparvin@gmail.com

💼 LinkedIn: https://www.linkedin.com/in/torkan-parvin

Thanks for stopping by! Feel free to explore my repositories, and if you have any questions or would like to connect, I'd be happy to hear from you.