Bengaluru, Karnataka, India
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About

Experienced Sr. Product Manager with 7+ years in driving product growth and monetization…

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Experience & Education

  • Pocket FM

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Volunteer Experience

Projects

  • Analyze This 2015, American Express

     Analyzed observations of 42000 citizens using given data set of 30 variables and predicted the chances of winning of competing parties
     Performed data refining and variable selection to choose optimal variable out of given 30 variables
     Built a classifier model using Generalized Boosting Model (GBM) to predict vote of an individual voter and finally winner of the elections

  • Forest Cover Type Prediction | Kaggle

     Developed insights on cartographic variables and implemented feature engineering to extract relevant features out of given 55 features
     Performed EDA, Correlation matrix and ANOVA test for visualization, trained random forest on train data set and achieved a maximum accuracy of 73%

  • Finite Element Analysis : Cantilever Beam

     Worked on ANSYS-mechanical software for numerically solving different type of beam problems
     Analysed the physical properties of cantilever beam with or without point mass load , calculated
    numerically, experimentally and through ANSYS
     Analysed the error produced while calculating the properties experimentally and by solving the problem with the help of ANSYS

  • Bike Sharing – Forecast Bike Rental Demand | Kaggle

     Performed variable manipulation using data visualization techniques and correlation matrix for constructing the model.
     Trained a random forest classifier on the significant parameters and achieved accuracy up to 80%

  • Titanic – Prediction of likelihood of Survival of Passengers | Kaggle

     Developed insights on correlations and significant variables for prediction of survival of passengers after pre-processing the training data
     Applied regression model and machine learning algorithms ( Random forest) to achieve the maximum accuracy of 78.5

  • Case Study on E-Commerce and Flipkart’s Business Strategy | Inter-hall Case Study Competition at IIT Kharagpur

     Studied major Watershed Milestones in Flipkart’s journey on the basis of 29 crucial events during their growth using Exploratory Data Analysis
     Analysed 28 Trends observed in online shopping and E-Commerce in India using Correlation Analysis, Hypothesis Testing and Google Trends in India
     Performed Competition Analysis of Flipkart on the basis of HHI indices, TARGET analysis, Uppity number and e-commerce market segmentation
     Charted the Flipkart’s competencies & resources…

     Studied major Watershed Milestones in Flipkart’s journey on the basis of 29 crucial events during their growth using Exploratory Data Analysis
     Analysed 28 Trends observed in online shopping and E-Commerce in India using Correlation Analysis, Hypothesis Testing and Google Trends in India
     Performed Competition Analysis of Flipkart on the basis of HHI indices, TARGET analysis, Uppity number and e-commerce market segmentation
     Charted the Flipkart’s competencies & resources to tap market opportunities

Languages

  • English

    Native or bilingual proficiency

  • Hindi

    Native or bilingual proficiency

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