Farhan Hussain

Data Science Intern at SkillCraft Technology

Gained hands-on experience in data preprocessing using real-world datasets, including handling missing values, data transformation, and feature engineering to enhance model performance and input quality. Conducted exploratory data analysis to uncover key patterns and insights. Built and evaluated ML models (e.g., Random Forest, Logistic Regression) to improve prediction accuracy and data quality. Created data-driven insights through visual reports and dashboards to inform business decisions.

Data Visualization Associate at Excelerate

Led a group of 16 teammates as Team Lead and Project Lead; managed project planning, delegated responsibilities, and ensured timely submission of high-quality deliverables. Used PostgreSQL for data cleaning and exploratory data analysis, and designed interactive dashboards in Looker Studio to showcase performance trends and key business metrics. Achieved a 360-degree performance score of 85%, demonstrating leadership, ownership, communication, collaboration, and problem-solving.

Independent Project at IPL Prediction Using Machine Learning Algorithms

Built ML models (Random Forest, Decision Tree, etc.) to predict IPL match outcomes. Engineered features and handled missing data to improve model reliability and accuracy. Identified key predictors such as strike rate, wickets, economy, and match venue. Selected Random Forest as the best-performing model for balanced accuracy and interpretability.

Independent Project at Netflix TV Shows and Movies Analysis

End-to-end analysis using SQL and Power BI; identified dominant genres, top content-producing countries, and release trends. Highlighted post-2015 content growth and trends in Drama/Action categories. Provided insights to inform content strategy and audience targeting.

Independent Project at Airline Passenger Satisfaction Analysis

Processed large datasets to ensure quality and consistency. Applied advanced classifiers (XGBoost, Random Forest) for high accuracy in predicting satisfaction. Identified key drivers such as business travel, class, and flight Wi-Fi. Performed feature selection to optimize model performance and interpretability.

Data Visualization Associate at Accelerate

Utilized PostgreSQL for data cleaning and exploratory data analysis (EDA), and employed Looker Studio to design interactive dashboards that showcased performance trends and key business metrics.

IPL Prediction Using Machine Learning Algorithms at GitHub Link

Built ML models to predict IPL match outcomes; engineered features and addressed missing data to improve model reliability; selected a balanced, interpretable model for prediction.

Netflix TV Shows and Movies Analysis at GitHub Link

End-to-end analysis of Netflix catalog using SQL and Power BI; identified dominant genres, top content-producing countries, and release trends; provided insights to inform content strategy.

Airline Passenger Satisfaction Analysis & Prediction using ML at GitHub Link

Processed large datasets for quality and consistency; applied classifiers (XGBoost, Random Forest) for high accuracy; identified key drivers such as Business travel, Class, and flight Wi-Fi; performed feature selection to optimize model performance.

Newspaper Survival in Post-COVID Digital Era (CodeBasics Challenge) at GitHub Link

Built and managed MySQL databases to analyze circulation and revenue; executed advanced SQL queries and data cleaning to extract key business insights; recommended data-driven digital transformation and revenue optimization.