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Data Science with less than a year in Data Analytics, Power BI, and Python.
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Data-driven MCA graduate skilled in SQL, Python, Power BI, and Excel built a $57M revenue dashboard and a segmentation model across 2M+ records with 28% retention uplift. Ready to partner with product, marketing, finance, and operations teams to turn complex data into clear, actionable business insights.
MIT World Peace University
MCA
August 1, 2023 – June 30, 2025
Mathuradas Mohota College of Science
B.Sc. · Computer Science
August 1, 2019 – June 30, 2022
GameCloud Technologies
Game Development Intern
February 1, 2025 – May 31, 2025
Pune, Maharashtra, India
Customer Segmentation using K-Means Clustering
January 1, 2026 – Present
Led customer segmentation using K-Means on RFM data from 500K+ transactions, identifying 5 high-value segments to drive targeted marketing campaigns and business decision-making. Orchestrated end-to-end ETL/ELT pipeline with Pandas, NumPy, and Matplotlib for EDA, feature scaling, and preprocessing handling 2M+ records for production-level clustering. Validated model with Elbow Method and Silhouette Score (0.72), delivering 28% customer retention uplift and measurable marketing ROI gains.
Credit Card Financial Dashboard
January 1, 2026 – Present
Developed an interactive Power BI dashboard analyzing $57M YTD revenue (+28.8% WoW growth) from SQL transaction data, enabling executive-level drill-down analytics across regions and segments. Engineered DAX measures and calculated columns for customer segmentation (Males: $31M vs. Females: $26M) and regional volume insights (TX/NY/CA: 68% of total transactions). Managed end-to-end data integration from SQL into Power BI with refresh schedules and model stability checks - directly supporting data-driven business decisions.
Google Play Store Data Analysis & Dashboard
January 1, 2026 – Present
Performed full-cycle EDA and data wrangling on 10,000+ Play Store records resolving missing values, duplicates, type inconsistencies, and outliers across Rating, Price, Reviews, and Installs. Applied multi-step data cleansing pipeline: sanity checks (reviews > installs), format standardization, mode imputation, and 95th-percentile outlier capping to ensure data integrity. Built an interactive Power BI dashboard (6,595 apps, 11bn installs, avg. rating 4.17) with KPI cards, category rankings, and monetization analysis enabling actionable insights for app publishers.
Data Analytics Masters
Udemy
June 1, 2026 – Present
Programming for Everybody (Python)
Coursera
June 1, 2026 – Present
IoT-Enabled Protective Healthcare
IJRTI
April 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong alignment with data science and analytics roles, covering customer segmentation, financial analysis, and app store insights. The breadth of tools and techniques used (Python, SQL, Power BI, Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, Tableau) indicates a willingness to learn and apply diverse technologies. The internship, while in game development, involved performance data analysis, which aligns with a data-driven mindset. The candidate is currently pursuing an MCA, indicating a commitment to continuous learning and professional development.
Soft Skills & Operational Fit
The candidate demonstrates an ability to collaborate in cross-functional teams and adhere to structured workflows, as evidenced by their internship experience. Project descriptions indicate a results-oriented approach with a focus on delivering measurable business impact (e.g., 28% customer retention uplift, $57M YTD revenue analysis).