An avid learner, I am an experienced Data Scientist with over 5 years of experience in applying analytics to retail, healthcare and manufacturing domain.

Being a part of reputed multinational corporations, I have the experience of working across diverse cross-office and cross-functional teams, handling clients and on-boarding new members to the project.

Tools 

Python, R, SQL, SAS, Tableau, QlikSense, PowerBI, GCP, AWS

Statistical/Business Skills

A/B Testing, Machine Learning, Regression, Survival Analysis, Classification, Segmentation, Deep Learning, ETL

Relevant Coursework

Statistical Computing, Statistical Methods, Data Management, Simulation Modeling & Methods, Probability Modeling, Data Visualization

Certifications

• Advanced Analytics Learning Program by International School of Engineering(INSOFE) 

• Statistical Thinking for Data Science and Analytics, Machine Learning for Data Science and Analytics by Columbia – edX

• The Analytics Edge by MIT – edX

• Communicating Strategically by Purdue - edX

Microsoft

Data Scientist II Aug '21 - Present

• Reduced scorecard generation time by 4% by cleaning up guardrail metrics and untagging histograms for redundant metrics

• Predicted early signals for churn of a customer on edge browser for an experiment with 86% precision. Scaled to multiple experiments

• Automated retention report using PowerShell script to save 35% time on running the retention reports manually

• Serve as an experimentation champ for experiments on Edge Browser. Working with feature teams to set up experiments, execute them and read scorecards

• Working cross-functionally across product management, marketing, data engineering, UX research, design, and operations teams to develop and customize solutions for customers 

Veeva Systems

Data Scientist Jul '20 - Aug '21

• Researching and Developing data science methodologies to add features to a SaaS product and scaling it through a streamlined production process in python

• Propensity score modeling based on 600 variables using regularized logistic regression and using these scores to perform test-control matching for hypothesis testing on marketing campaigns

• Predicting sales volume of products by creating a cascade of machine learning models. Creating confidence intervals for the predicted volume through resampling and using appropriate distributions

KMK Consulting

Senior Analyst - Data Science, Analyst - Data Science May '18  - Jun '20

• Predicting customer churn: Improved sales forecast accuracy by 7% by predicting customer churn from a product using Recursive Neural Networks (RNN) and implemented through Tensorflow on Python. Presented results to top management.

• Survival Analysis of customers: Projected revenue through duration analysis of customers while helping client transition from Teradata to Hadoop (MapReduce) to Spark framework increasing data processing efficiency by more than 10x.

• Product analytics: Defining and measuring over 20 KPIs for a new product including adoption, growth, and churn

• Received award for demonstrating exceptional personal accountability while working with critical clients

Procter and Gamble

Data Science Intern Sep '17  - May '18

• Predicting lost sales: Building Bayesian Probabilistic model (Markov Chain Monte Carlo) to predict lost sales for Procter and Gamble with a potential to save $2B per year for the company

ZS Associates

Decision Analytics Associate May '15  -  Apr '18

• Targeting and Segmentation: Improved reach by 30% through effective targeting and segmentation of key customers

• Employee Churn Modeling: Analyzed HR data for ZS to discover primary factors for employee churn in the company. Created a decision-tree based model to predict upcoming employee churn allowing HRs to take corrective action

• Data Science Community @ZS: Contributed to company’s Data Science learning community and Toastmaster’s club, thus, contributing to professional development of peers through collective learning and sharing

Saint-Gobain India

Data Analyst Jul'14  -  May '15

• Identified and reduced alarms by 40% by deep dive analysis of the system using a fish-bone approach

• Worked on identifying issues in the automated manufacturing system using data analysis

University of Cincinnati - Carl H. Lindner College of Business

Master of Science in Analytics Aug '17 - Aug '18

National Institute of Technology Jalandhar

B. Tech in Engineering Jul '10 - Jun '14

Certificates:

• Product Strategy Certificate

• Kellogg Executive Education