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Data Analyst Python

Chennai, Tamil Nadu, India
May 22, 2020

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*, ***** ****** ***** **** ROAD, PUZHUTHIVAKKAM, CHENNAI-600091

Email: +91-934******* +91-893*******


Madras Institute of Technology, Anna University, Chennai, India June 2019 Bachelor of Automobile Engineering (CGPA 9.13/10)

Relevant course work Computing Techniques, Math with Advanced Calculus, Linear Algebra with matrices Honor: Awarded Full Scholarship from the MIT Alumni Association for consistency in academics 2015-19 New Prince Matriculation Higher Secondary School (Overall 97.58%) April 2015

HSC with Major in Math (100%), Physics (99.5%) and Computer Science (99.5%) New Prince Matriculation Higher Secondary School (Overall 97.6%) April 2013

SSLC (10


grade) with Major in Math (100%) and Science (98%) SKILLS

Python (Pandas, scikit-learn, nltk tensorflow etc.), MySQL, MS EXCEL, MATLAB, MS Powerpoint, Tableau, C & C++ from NPETL Course by IIT Bombay (S.No: 630838RPJO) PROFESSIONAL EXPERIENCE

Vola Finance Internship Mar 2020 – Present

Data Analyst Banglore

Feature Extraction for generating the top 20 of 1431 variables to classify defaulters and very good users using Logistic Regression and Random Forest Classifier with IV_XG Boost

Used nltk package to analyze the reviews of the app from various platforms (such as Appstore, Playstore

& other sites) through web scraping in Python and presented them in the form of Word cloud to showcase the most important problems that needed immediate action. Daimler India Commercial Vehicles Private Limited Jan 2019 – May 2019 BS VI Project Management Intern Chennai

Worked as Project Manager managing BS-VI R&D Project by coordinating teams, following up activities through meetings, communicated progress & decisions to be taken to the higher management presentations

Tools used: MS Power Point and Excel

Rane Madras Limited Internship Jul 2018 – Aug 2018 Inventory Forecast Kancheepuram

From past 6 year monthly demand data for engine parts, populated a matrix of series of demand for every product in the past with split up as training and testing data

Built ML model with Decision Tree classifier with outlier detection and control, trained, tested the forecast accuracy & compared it with traditional ARIMA and moving averages methods in Python PROJECTS

Kaggle Breast Cancer Prediction Competition Apr 2020

Built predictive models with various ML algorithms to predict whether a patient has cancer or not. Obtained AUC of 0.82 with Random Forests and used 10 fold cross validation for hyper parameter tuning in Python

Kaggle Titianic survival Prediction Competition Mar 2020

Used data wrangling to account for missing values in the dataset, selected features that are useful in prediction by visualizing each variable against the target, combined and extracted features from certain columns.

Built various ML models and tested the accuracy of prediction & finalized the Random Forest to be the best model with 86% accuracy


Deep Specialization from Harvard University (Ongoing course) Topics Covered: ANN, CNN, RNN, Improving Neural Networks and Sequence models Projects: Google Stock Price Prediction with LSTM Recurrent Neural Networks, Image classification with MNIST dataset and Boston House Price Prediction with ANN

Machine Learning A-Z: Hands-On Python & R for Data Science from Udemy course Topics Covered: Data Preprocessing, Regression, Classification, Clustering, Association Rule Learning, Reinforcement Learning, Natural Language Processing, Deep Learning, Dimensionality Reduction(PCA

& LDA), Model Selection and boosting(Hyper-parameter tuning, Cross Validation) Projects: Predicting the spending score of user from the data of previous customers in a store. Classified users into various categories depending on whether the new product would be of their potential interest

Advanced MySQL for Business Intelligence

Topics Covered: Multi-level Querying, JOINS, Creating Temporary Tables & basic database design features

Projects: Analyzed a large database of website transactions & orders and provided various insights with funnels, necessary for portfolio optimization and bidding costs for the website campaigns driving traffic, analyzed the growth of company over the period and provided feedback as to implement the most desirable changes.


Organizer & Committee member of various technical events in SPARK 2017 and AUTOMEET 2018 National Level Symposiums attracting more than 250 participants

Volunteered in Youth Red Cross (YRC) activities in college

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