Well rounded, visionary data scientist with broad spectrum of domain expertise, technical knowledge, and proven success in leveraging data into actionable insights.
Data Scientist, 07/2016 to Current Udacity – Mountain View, CA
Developed model to predict Nanodegree and implemented pipeline to send email on a weekly basis to students.
Created a model that finds out related courses and Nanodegree to a given course and deployed on Udacity website.
Performed extensive analysis on performance of coupon and provided recommendations to CEO about targeting students with coupons in future.
Produced and managed content health analysis which helped course developers get useful insights about performance and difficulty of each concept in a course.
Worked extensively on data pipelines to aggregate data from different sources.
Sr. Data Scientist, 08/2015 to 07/2016 Ebay Inc – San Jose, CA
Developed and implemented a modeling methodology that modifies random forest for uplift modeling to optimally
picks users who will purchase due to incentive as opposed to users who will buy no matter what.
Partner with Lower Funnel and Coupon Business unit to identify, develop and implement targeting improvements to optimize
coupon spend and obtain a better return over investment for different cohorts.
Managed a team of geographically distributed data scientists supporting the global CRM function.
Responsible for the global CRM data science project pipeline. Worked closely with global business partners to identify, develop
and implement targeting improvements across various Internet marketing channels that led to $90M/year incremental revenue.
Built a recommendation engine (loosely based on collaborative filtering) to surface inspiring and relevant product to users.
Improved A/B test designs that resulted in roughly 30% more tests reaching significance.
Data Scientist, 02/2014 to 02/2015 Ebay Inc – San Jose, CA
Developed a model to predict user's propensity to purchase an item on eBay.com on a given day using R & SQL.
Used model selection techniques like AIC, BIC criteria to make the model parsimonious.
Led the development of the first successful product category level propensity to buy model.
Scores from the model are used to
customize content on the website, including watched items and billboard, which show 100% CTR and 20% attributed purchase
Helped eBay Loyalty Program team understand causal effect of this program and provided recommendation on users to target to
send an invite for it. Coarsened exact matching was used to remove bias and obtain causal effect of incremental revenue.
Movie Recommendation System, 02/2013 to 03/2013 Columbia University Project – New York, NY
Formulated a model to recommend movies to a million users depending on their subscription and ratings.
Visualized the data using MDS technique and created a dissimilarity matrix to observe clusters.
Predictive Modeling for Email Spam Detection Using Machine Learning (Python.
Predictive Email Spam Detection, 02/2013 to 03/2013 ColumbIa University Project – New York, NY
Analyzed 10000 users' dataset to detect spam emails using various Machine Learning Generative models.
Evaluated the best technique as Naïve Bayes using model selection and validated the model using ROC curves.
Predicted the detection system accurately with an estimate of generalized error to be as small as 3%.
Master of Science: Operations Research, December 2013 Columbia University - New York, NY Coursework - Analysis of Algorithms, Machine Learning, Optimization Methods and Models, Stochastic Processes, Linear Regression Models, Mathematics of Finance, Risk Management, Simulation, Advanced Machine Learning.
Coursework - Analysis of Algorithms, Machine Learning, Optimization Methods and Models, Stochastic Processes,
Linear Regression Models, Mathematics of Finance, Risk Management, Simulation, Advanced Machine Learning.:
Bachelor of Science: Electronics and Telecommunication, June 2012 University of Mumbai - Mumbai
Electronics and Telecommunication Capstone Project - Implemented Stock Market Prediction using Neural Networks in MATLAB (Machine Learning) to
achieve accurate predictions and improved average rate of return and Sharpe ratio by 16% and 75% respectively.
Honors/Awards - Felicitated with Sir Dorabji Tata scholarship in freshman and sophomore years.
Introduction to Big Data using Apache Spark (edX, Summer 2015)
Scalable Machine Learning (edX, Summer 2015)
Recipient of critical Talent Award at eBay Inc in 2016.
Master of Science : Operations Research , December 2013 Coursework - Analysis of Algorithms, Machine Learning, Optimization Methods and Models, Stochastic Processes,
Linear Regression Models, Mathematics of Finance, Risk Management, Simulation, Advanced Machine Learning. : Bachelor of Science : Electronics and Telecommunication , June 2012
Create a job alert for [job role title] at [location].