Projects & Works
NovaMart improves sales forecast accuracy by 28%.
September '24
NovaMart, a mid-sized retail chain, struggled with unpredictable sales patterns across its regional outlets. By analyzing three years of transaction data using SQL and Python, I designed a predictive model that identified seasonal trends and regional variations.
The model was deployed into Tableau dashboards, allowing managers to forecast weekly demand more precisely. As a result, NovaMart improved its forecasting accuracy by 28%, reduced excess stock by 15%, and minimized product shortages, leading to more consistent revenue growth.
Lowers customer churn rate by 15% for Finexa
June '24
Finexa, a digital payments startup, was facing high customer churn due to inconsistent usage patterns. I gathered and cleaned over 80,000 transaction records to uncover behavioral indicators of churn. Python clustering techniques helped segment customers into actionable categories.
By visualizing insights in Tableau dashboards, the marketing team gained a clear picture of at-risk customer groups. Targeted campaigns were launched, improving engagement rates and successfully lowering the overall churn rate by 15% within a single quarter.
OptiFab saves $950K yearly through data insights.
March '24
OptiFab, a mid-sized manufacturing brand, was facing rising costs due to delays and inefficiencies in its assembly process. To tackle this, I consolidated production data from multiple ERP systems and designed a Python-based ETL workflow that automated reporting and highlighted performance bottlenecks.
Experience & Education
Data & Business Analyst Intern
InsightWorks Analytics
Worked on real-world datasets to support sales and operations teams with insights. Gained hands-on experience in SQL, Python, and Tableau by building dashboards, automating reports, and presenting findings to senior managers.
Master of Science (Computer Applications)
TechVille University • CGPA 9.0 / 10
Focused on advanced programming, database management, and business intelligence. Coursework included machine learning, data visualization, and applied statistics. Completed a final-year project on predictive modeling for retail data, achieving 92% model accuracy.
Bachelor of Science (Computer Applications)
Metro City College • CGPA 8.7 / 10
Built a strong foundation in programming, databases, and software development. Developed multiple academic projects, including a student management system and a small-scale analytics dashboard using Python and MySQL.
Interest & Expertise
Tool and Language
Python
Applied Python for data cleaning, visualization, and automation, using libraries like Pandas and Matplotlib. Built scripts to reduce manual work and speed up business reporting.
SQL & Databases
Experienced in writing optimized queries and managing datasets of 50k+ records. Used SQL for reporting, segmentation, and preparing inputs for machine learning models.
Tableau & Power BI
Designed interactive dashboards to communicate business insights. Enabled teams to track KPIs like churn rate and sales growth in real time, helping managers make quick decisions.
Interest
Business Intelligence & Data Analytics
Strong passion for extracting insights from complex datasets. Focused on solving business challenges such as churn, forecasting, and customer segmentation through data-led approaches.
Machine Learning Applications
Explored predictive modeling techniques like regression and clustering. Built academic projects applying ML to retail and finance datasets with accuracy rates above 90%.
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