Jatin Mehta Email & Phone Number

California, United States

New York, NY, US

New York, NY, US

Phoenix, AZ, US

• Tools & Languages: Python, Tableau, Machine Learning
• Developed interactive charts using Tableau to visualize key parameters associated with delinquent retailers and performed EDA using python to create new features to improve the prediction accuracy of delinquency
• Created predictive model to determine delinquent lottery retailer accounts using Decision Tree, Random Forest, Gradient Boosting classifier and performed K- means clustering to segregate low, medium and high-risk.

Noida, Uttar Pradesh, IN

• Developed new risk models for underwriting using XGBoost on spark-distributed clusters for generating credit scores of customers which reduced bad debts by 20%
• Deployed recovery model using ensemble learning (XGBoost & Light GBM) with 84% AUC and helped the collection team in reducing losses by 15%
• Leveraged data of 400Million+ users for engineering features, modelling and developing credit policies using Univariate analysis to determine the most important features and new features ideas for optimizing risk.
• Executed growth marketing and customer targeting plan which resulted in an increase in the acquisition of new user base from 1 Million to 10+ Million users in a period of 6 months
• Improved and optimized the PnL of Digital Gold category by optimizing the growth campaigns and reducing the spends by launching customer-centric campaigns and ecosystem promotions
• Implemented automated retargeting of users dropping out at various stages of the funnel to convert them into transacting users growing the overall funnel conversion rate by 50%

Noida, Uttar Pradesh, IN

• Growth of Mobiles Category at Paytm Mall fueling strategic decision making by derivation of data-based insights and optimizing the effectiveness of each campaign entailing the cashback offers, communication, marketing.
• Designed Regression Model to identify key drivers to achieve higher category GMV at a significantly lesser use of resources like Cashback and Visibility
• Studied and classified the customer base of 300 Mn into various segments based on features like Paytm evolved, customer affluence, affinity, users’ demographics, funnel drop-offs etc. to optimize push notifications.
• Augmented inventory fill rate at the frontend by 19%; enabling quick replenishment via automated alerts
• End to end analysis on different aspects of category management like Growth, Supply, Customer Experience, On-boarding, Cataloging, Payments etc.
• Drove product improvement features to enhance the user experience, traffic and conversion in coordination with multiple teams

Noida, Uttar Pradesh, IN

• Formulated Key Performance Indicators and suggested product improvements for categories by identifying possible layers of funnel enabling tracking of consumer activities using Google Analytics
• Designed and Automated organization-wide analytics reports like category wise conversions and GMV, re-engagement performance, cohort analysis which gave the complete topline funnel visualization using tools like R.
• Rolled out the cart abandonment model for Paytm Mall which aimed at notifying customers on their cart status by sending a push notification, in turn boosting the central level revenue by ~ $1.5 million per month
• Worked on Text Mining using twitter data to suggest product improvements and fixes tackling heavy traffic and categorize the customer feedbacks into positive, negative or neutral sentiments
• Delivered Google Analytics training sessions - both Paytm wide and team-specific.
• Implemented Google Analytics for Paytm e-commerce app, Internal search tracking, grid performance tracking, custom funnel tracking, internal promotion tracking and custom business tracking by consulting category.

New Delhi, Delhi, IN

-Interned at the commodities and currency department- Analyzed and researched on the various commodities and currencies using the terminals like Thomson Reuters and Metastock charts-Performed fundamental analysis of Agri and Metal commodities and compiled findings in a project report

IN

-Interned at the Operations and Logistics division. Studied the company’s heuristic for machine scheduling- Collected empirical data for processing, setting and transportation times and used it to forecast a reduction of 11.15% in make-span time by converting the flow shop into a parallel shop-Implemented the scheduling algorithm on five different types of.

Master Of Science - Ms, Business Analytics

Bachelor Of Engineering (B.E.), Manufacturing Processes And Automation Engineering(M.P.A.E.)

Class Xii

Class X