Currently an Extern @Mangusta CapitalMaster's student in Data Science with early-career experience and an externship in deal sourcing and startup analysis at Mangusta Capital.
Projects and analyses focused on sourcing opportunities and evaluating startups, combining data science methods with market and deal research from my Mangusta Capital externship.
Analyzed e-commerce transaction data using Python to identify sales, customer, product, and marketing trends. Performed data cleaning, EDA, feature engineering, and correlation analysis to evaluate business performance. Identified a 0.0104 correlation between advertising spend and revenue, supporting data-driven marketing decisions.
Analyzed 10,000 bank customer records to identify key factors influencing customer churn. Performed data preprocessing, EDA, categorical encoding, feature engineering, and SMOTE for class balancing. Built and evaluated Logistic Regression, Random Forest, and XGBoost models, achieving 82% accuracy and 0.84 ROC-AUC with Random Forest.
Master's student in Data Science with early-career experience and an externship in deal sourcing and startup analysis at Mangusta Capital.
I am Varikuppalabharath Kumar, a graduate student pursuing a masters degree in Data Science. I started my career and am exploring a career change while gaining practical experience through a Mangusta Capital Deal Sourcing & Startup Analysis externship.
Externships
Mangusta Capital Deal Sourcing & Startup Analysis Externship
Mangusta Capital
Experience
Micro-Internship Intern, AI Consultant
Kyndryl (via Springpod) · July 2026
Education
Gisma University of Applied Sciences
Master of Science in Management —Current Grade: 1.9
South centrail Railway Degree college
Bachelor of science Overall Percentage: 76.3
Skills
Analyzed e-commerce transaction data using Python to identify sales, customer, product, and marketing trends. Performed data cleaning, EDA, feature engineering, and correlation analysis to evaluate business performance. Identified a 0.0104 correlation between advertising spend and revenue, supporting data-driven marketing decisions.
Analyzed 10,000 bank customer records to identify key factors influencing customer churn. Performed data preprocessing, EDA, categorical encoding, feature engineering, and SMOTE for class balancing. Built and evaluated Logistic Regression, Random Forest, and XGBoost models, achieving 82% accuracy and 0.84 ROC-AUC with Random Forest.
✅ Verified by Extern · ⏱️ In progress
Join a new VC fund launched by a former SoftBank Vision Fund leader and backed by the Ray-Ban/Oakley family to identify high-potential Vertical AI startups. Gain hands-on experience sourcing deals, analyzing markets, and writing compelling investment memos.
The externship sourced and analyzed Vertical AI startups for an early-stage VC fund. Work combined market research, deal screening, and investment memo writing. Deliverables included investment-grade diligence materials and a completed investment memo for a target startup.
I worked across deal sourcing, market analysis, and investment memo preparation. Below are the concrete pieces I produced during the externship.
