Transforming raw data into actionable insights through analytics, visualization, and machine learning.
Currently pursuing MCA at VIT Vellore, I am building a strong foundation in Data Analytics, Machine Learning, Software Development, and core Computer Science concepts. My work primarily involves SQL, Python, Java, ML, Power BI, data visualization, and analytical problem-solving, with a focus on applying technology to real-world challenges.
Through hands-on projects, I have worked on revenue and retention analytics, customer behavior analysis, business intelligence reporting, predictive modeling, and machine learning applications using real-world business datasets. These experiences have strengthened my ability to work across the complete data lifecycle from data preparation and analysis to visualization, model development, and business interpretation.
I am particularly interested in how data, technology, and business strategy come together to drive growth, improve operational efficiency, and support better decision-making. Beyond analytics, I have a strong interest in machine learning, artificial intelligence, and building technology-driven solutions that create real value.
MySQL • Python • Pandas • Excel • Power BI • DAX
End-to-End Customer, Revenue & Subscription Analytics Platform
A comprehensive analytics solution built using a real-world SaaS customer dataset to monitor revenue performance, customer retention, subscription behavior, and churn risk through executive dashboards and advanced SQL analytics.
- Analyzed 7,043 customer records across multiple business dimensions.
- Performed 30+ SQL analyses covering segmentation, cohort analysis, retention, and revenue intelligence.
- Developed 20+ DAX measures and 5 interactive Power BI dashboards for executive KPI tracking.
- Discovered key business insights, including 45.3% churn among Electronic Check users and 56.4% revenue from Month-to-Month customers.
Python • Pandas • NumPy • Power BI • DAX
Interactive Executive Dashboard for Quick Commerce Analytics
Designed an end-to-end business intelligence solution that transforms operational and customer data into executive-ready dashboards for monitoring business performance, customer behavior, product performance, and operational efficiency.
- Processed 500K+ orders, 3.4M+ transactions, and 49K+ products.
- Analyzed purchasing behavior across 160K+ customers.
- Designed a Star Schema with 3 Fact Tables and 3 Dimension Tables for scalable analytics.
- Developed 15+ KPIs and a 4-page Power BI dashboard covering Executive, Customer, Product, and Operations Intelligence.
- Identified VIP customers contributing 44% of total revenue, enabling targeted retention strategies.
Python • Pandas • NumPy • Scikit-Learn • Matplotlib • Streamlit
Machine Learning-Based Academic Performance Prediction Platform
Designed an end-to-end machine learning solution that predicts student performance, discovers learning patterns through clustering, and generates personalized learning recommendations to support data-driven educational decisions.
- Predicted student performance using Random Forest Classification with 83–85% accuracy.
- Applied K-Means Clustering to identify student learning patterns.
- Performed data preprocessing, feature engineering, and categorical encoding.
- Built a personalized recommendation engine for academic improvement.
- Developed an interactive Streamlit application for real-time predictions.
Python • Pandas • NumPy • Scikit-Learn • Joblib • Streamlit
Procurement Analytics & Invoice Risk Prediction Platform
Developed a machine learning solution for procurement analytics that predicts freight costs and identifies high-risk invoices, helping organizations improve purchasing decisions and operational efficiency.
- Built a Freight Cost Prediction model using Regression algorithms.
- Developed an Invoice Risk Flagging model using Decision Tree Classification.
- Achieved:
- R² Score: 0.97 for freight cost prediction.
- 82% Classification Accuracy for invoice risk detection.
- Evaluated multiple ML models using GridSearchCV and Cross Validation.
- Delivered predictions through an interactive Streamlit web application.
I'm always open to connecting with students, professionals, recruiters, and fellow tech enthusiasts.
Whether you'd like to discuss Data Analytics, Machine Learning, projects, internships, or collaboration opportunities - feel free to reach out!
📧 Email: arjun11goel@gmail.com
💼 LinkedIn: https://linkedin.com/in/arjun11goel
💻 GitHub: https://github.com/arjun11goel