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Updated 2 years ago


Masters candidate in data science currently interning at United Healthcare Group. 3+ years of experience in building end-to-end data-driven products. Strong background in statistics and machine learning. Interested to apply Machine Learning and Deep Learning skills to industry to solve exciting new problems.


  • Product Management
  • Python
  • R Programming
  • SQL


July 2017 August 2018

Masters of Data Science at University of San Francisco

Relevant Coursework:
Machine Learning, Distributed Computing, Time Series Analysis, Probability and Statistics, Linear Algebra, Data Acquisition, Linear Regression, A/B Testing, Computational Statistics

Technical Skills:

Random Forest, Gradient Boosting Models, Clustering (K-Means, Spectral), Collaborative Filtering, Linear and logistic regression, Neural Nets (CNN, RNN, LSTM)

Spark, Pytorch, Keras, MongoDB

Python, R, SQL

August 2010 July 2014

B.Tech. in Aerospace Engineering at Indian Institute of Technology, Madras

Relevant coursework:
Calculus, Differential Equations, Linear Algebra & Numerical Analysis, Process Optimization, Complex Variables and Transform Techniques, Multivariate Data Analysis for Process Modeling, and Probability, Statistics & Stochastic processes


October 2017

Data Scientist Intern at UnitedHealthcare Group

Project: Categorizing customer reviews
• Identified and quantified main customer issues from freeform web surveys responses through topic modeling
• Engineered features using natural language processing techniques, implemented classification model on web survey data to identify key factors that affect the net promotion score (NPS)
Project: Rejection Claims Analysis
• Identified business-critical factors that cause long waiting time for an approval of health insurance claim, by experimenting with features and machine learning models
• Predicted the resolution time of an insurance claim with an accuracy of 85% with a 5-layer Deep Neural Network
• Processed ~620K customer episodes from 18M claims transactions based on key business metrics using SQL

February 2016 June 2017

Data Scientist, Forecasting at Merck Sharp & Dohme Pharmaceutical

Python: Pandas, Numpy, Scipy, Scikit-learn, PyQt; Techniques: Time Series Analysis
Project: Application development
• Developed an automated data cleaning and curve fitting tool based on Bass Model Diffusion curves using Python
• Built a web-based forecasting tool with interactive data visualization using R-Shiny that implements automated selection of forecasting techniques such as Holt-Winters, Box Jenkins (SARIMAX, VARX), exponential model

June 2014 January 2016

Business Analyst at Aspect Ratio, Global Centre for Analytics and Forecasting

Tools: Excel, VBA, Spotfire
Project: Oncology therapeutic area
• Led a team of 4 to design, develop and deploy a survival model to understand retention of patients in multiple patient cohorts; received a Five Star Award of Excellence from the client
• Conducted an Exploratory Factor Analysis to identify the underlying relationship between various parameters of launch product. Identified an analog based on similarity of its parameters with the launch product