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Big Data | AI/ML | Ad Tech
Grad student at USC majoring in Computer Science. I am keenly interested in creating and developing software that solves real-world problems. Passionate about leveraging data to make efficient decisions by predicting the future. Although most of my work experience revolves around designing data-driven software, I am open and excited to explore other areas as well. Actively looking for full-time job starting June 2020.
University of Southern California
Master of Science - MS, Computer Science
January 1, 2018 – January 1, 2020
Guru Gobind Singh Indraprastha University
Bachelor of Science - BS, Computer Science
January 1, 2014 – January 1, 2018
St. Xavier School - Delhi
High School Certificate, Non-Medical
January 1, 2013 – January 1, 2014
PubMatic
Senior Product Analyst - Monetization
November 1, 2024 – Present
PubMatic
Software Engineer 2 - Big Data
June 1, 2023 – October 1, 2024
PubMatic
Software Engineer - Big Data
February 1, 2021 – June 1, 2023
Insight Data Science
Technical Advisor
November 1, 2020 – February 1, 2021
Insight Data Science
Data Engineering Fellow
June 1, 2020 – February 1, 2021
Koder
Software Engineer Intern
January 1, 2020 – February 1, 2020
Irvine, CA
Activision
Software Engineer Co-op
May 1, 2019 – January 1, 2020
Santa Monica, California
University of Southern California
Course Grader
September 1, 2018 – May 1, 2019
Greater Los Angeles Area
So Delhi
Machine Learning Intern
January 1, 2018 – May 1, 2018
New Delhi
DataScribble
Co-Founder
June 1, 2017 – December 1, 2018
Probus Insurance Broker Limited
Data Science Intern
June 1, 2017 – July 1, 2017
Mumbai, Maharashtra, India
PolicyBoss
Data Analysis Intern
June 1, 2016 – July 1, 2016
Mumbai, India
Boston Housing Data Set
June 1, 2017 – Present
Solved the problem of predicting the median value of owner occupied houses in the suburbs of Boston. Language used: Python Algorithm used: Random Forests Accuracy ~ 80%
Charles Book Club
June 1, 2017 – Present
The data set represents information associated with individuals who are members of a book club. This is a model for predicting whether a person will purchase a book about the city of Florence based on past purchases or not. Language used: Python Algorithm used: Logistic Regression Accuracy ~ 92%
Kaggle Titanic Problem
June 1, 2017 – Present
Simple implementation of Random Forest algorithm using ScikitLearn in Python, rendering a score of 0.75120 on Kaggle.
Loan Status Prediction
June 1, 2017 – Present
Making a predictive model to automate the loan eligibility process in real time based on customer details provided while filling online application form. Algorithm used: RandomForest Accuracy ~82%
Stocks Price Prediction
June 1, 2017 – Present
Predicting the Stock Prices of Tesla Motors Stock Price data of 5 years used to predict next month prices. Language used: Python Algorithm used: Random Forests Accuracy ~95%
Mining and Analysis of Insurance Policies Customer Database
June 1, 2016 – July 1, 2016
Mining and Analysis of Insurance Policies Customer Database- Landmark Insurance Brokers Pvt Ltd This is a Data Mining and Analysis project. Technology used: MS-Excel
Cultural Fit Analysis
The candidate has a strong background in data science and machine learning, with experience in both corporate and startup environments. Their involvement in a data science blog and conducting sessions indicates a passion for the field and a potential for knowledge sharing. However, the recent role as 'Senior Product Analyst - Monetization' and previous 'Software Engineer - Big Data' roles, while data-intensive, might indicate a slight shift from a pure Data Analyst focus, requiring clarification on their current career aspirations. The project diversity is good, but the target role 'Data Analyst' might be a slight step back from their 'Software Engineer 2 - Big Data' role, which could impact long-term cultural fit if not aligned with growth opportunities.
Soft Skills & Operational Fit
The candidate's experience as a Co-Founder and Technical Advisor suggests leadership, communication, and problem-solving skills. Their work on various projects with reported accuracy improvements indicates a results-oriented approach. The diverse project portfolio also points to adaptability and a willingness to tackle different types of data challenges.