🎓 MCA Student at Thapar Institute of Engineering & Technology
I am an MCA student with a strong interest in Data Analytics, Data Science, and Software Development. I enjoy transforming raw data into actionable insights, solving business problems through analytics, and continuously improving my technical skills through hands-on projects.
My current focus is building a strong portfolio in Data Analytics and Machine Learning while preparing for internships and full-time opportunities in Data Analytics, Data Science, and Software Development.
- Python
- SQL
- C++
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-Learn
- Git
- GitHub
- Jupyter Notebook
- VS Code
Skills Applied:
- Data Cleaning
- Exploratory Data Analysis (EDA)
- Data Visualization
- Correlation Analysis
- Insight Generation
Skills Applied:
- Business Analytics
- Feature Engineering
- KPI Analysis
- Time-Series Analysis
- Customer Analytics
- Product Performance Analysis
- Profitability Analysis
- Business Recommendations
Key Findings:
- Identified the highest-performing region and product category.
- Analyzed customer and product-level performance.
- Evaluated the impact of discounts on profitability.
- Generated business recommendations based on analytical findings.
Skills Applied:
- Customer Analytics
- Revenue Analysis
- RFM Analysis
- Customer Segmentation
- Customer Behavior Analysis
- Business Recommendations
Key Findings:
- Identified high-value customer segments using RFM Analysis.
- Analyzed customer purchasing behavior and spending patterns.
- Evaluated customer engagement through recency, frequency, and monetary metrics.
- Generated customer retention and loyalty recommendations.
Skills Applied:
- Marketing Analytics
- Customer Analytics
- Campaign Performance Analysis
- Customer Response Analysis
- Feature Engineering
- KPI Analysis
- Business Recommendations
Key Findings:
- Customers aged 70+ exhibited the highest average spending.
- Customers with PhD qualifications demonstrated the highest spending levels.
- Campaign 4 achieved the highest customer acceptance.
- The latest campaign achieved a response rate of approximately 14.94%.
- Physical stores remained the most preferred purchasing channel.
- Generated data-driven marketing recommendations to improve customer engagement.
- HR Analytics
- Supply Chain Analytics
- E-commerce Analytics
- Machine Learning Portfolio Projects
- Data Cleaning
- Exploratory Data Analysis (EDA)
- Data Visualization
- Feature Engineering
- KPI Analysis
- Customer Analytics
- Marketing Analytics
- RFM Analysis
- Customer Segmentation
- Business Insight Generation
- Business Recommendations
- Data-Driven Decision Making
- Analyzed over 550,000+ records across multiple real-world datasets.
- Built 4 end-to-end analytics projects from data cleaning to business recommendations.
- Applied customer analytics, marketing analytics, KPI tracking, business analytics, and customer segmentation techniques.
- Created professional visualizations and documented findings through GitHub projects.
- Developed structured analytics workflows aligned with real-world business problems.
- HR Analytics
- Supply Chain Analytics
- E-commerce Analytics
- Customer Churn Analysis
- Sales Forecasting
- Complete 6+ high-quality analytics projects.
- Strengthen SQL and Data Structures & Algorithms.
- Build a dedicated Machine Learning project portfolio.
- Maintain consistent GitHub contributions.
- Secure an internship or full-time role in Data Analytics, Data Science, or Software Development.
📧 Email: harshitpoonia31@gmail.com
- Data Analytics
- Data Science
- Marketing Analytics
- Customer Analytics
- Business Analytics
- Python Development
"The best way to learn is by building."