Data Analyst Engineer

Nikhil Agrawal

Machine Learning Engineer

****************@*****.***

980-***-****

nikhilagrawal328.github.io/nikhil.github.io/

linkedin.com/in/nikhil-agrawal-40471110b

github.com/nikhilagrawal328

EDUCATION

08/2015 – 06/2019

Bachelor of Technology - BTech

Guru Nanak Dev Engineering College

CGPA - 8

WORK EXPERIENCE

07/2018 – 11/2018

Data Analyst Intern

Untravel

Gurgaon

Automate their weekly and monthly emailers by building a recommendation system on their travel products.

Perform Data Analysis on sales data and presented a report on weekly basis.

03/2018 – 05/2018

Data Science Intern

CSIR- CDRI

Work From Home

Collect data for the venture capitalist who provides grants to the companies in USA from wikipedia, crunchbase etc. Analyze the funding for each of the category and finally presented a report on it.

07/2017 – 08/2017

Project Intern

Garima Software Solutions

Hyderabad

Build a web application that store all the users related data like academic details, account no, mobile no etc.

Users can able to modify or add new details through his login-id and password.

SKILLS

Python Machine Learning Deep Learning NLP

Data Structure & Algorithms Java AWS SQL

PERSONAL PROJECTS

KDD Cup 2009 Orange Customer Relationships

The Challenge is about predicting the propensity of customers to switch provider (churn), buy new products or services (appetency), make the sale more profitable (up-selling). Dataset is first cleaned, pre-processed, apply one-hot encoding on categorical data, perform feature selection and then apply MLP and CNN model to get higher score.

Loan Prediction Problem

Bank customer dataset is pre-processed, analyzed and machine learning regression model is built to predict the probability that the customer will default.

Stack Overflow Tag Prediction

Perform basic EDA and text pre-processing and finally build a logistic regression with one vs rest classifier model to predict the tags for each of the question posted on stack overflow site. Predicting Employee Churn

Employee dataset is analyzed and balanced using oversampling and then build a machine learning GBDT model to predict which employee will leave the company.

Predicting the number of cabs in each region of new york city

New york city taxi dataset is pre-processed, analyzed, clustered into regions and a machine learning regression model is built to predict the number of cabs in each region of new york city. RELEVANT COURSEWORK

Data Structure and Algorithms

Machine Learning

Natural Language Processing

Big Data and Analysis

INTERESTS

Gaming Comedy Cricket Books

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