Information Technology Active Directory

Summary

Adaptable System Analyst with * year of experience in interpreting and analyzing data in a fast-paced environment for driving business solutions. Proficient knowledge in Statistics, Machine Learning, and analytics.

Education

Rutgers The State University of New Jersey New Jersey, USA Masters in Business Analytics & Information Technology January 2017-May2018

University of Mumbai Mumbai, INDIA

Bachelor of Engineering in Information Technology August 2014

Technical Skills Other Skills

R Programming – Classification, Regression, Supervised and Unsupervised learning.

Python – Object Oriented, Data Analysis and Machine Learning.

Ad-hoc Analysis

Facebook Analytics, Google Analytics and Adobe Analytics

GitHub

Big Data – Parallel Computing & RDD with PySpark.

SAS

Tableau, QlikView, Looker, MATLAB

VMware VCP 5.5

Windows Server 2003/2008/2008R2/2012

MS Excel: Pivot Table, if else

MySQL, SparkSQL, PostgreSQL – Create, query and update databases, Triggers, Views, Aggregate Functions.

MS Word, MS PowerPoint

Microsoft Project, Visual Studio 2017

C++ - Classes, Function overloading, References, Pointers

Professional Experience

Client: Hewlett Packard January 2015 – January 2016

Managing & Administering Users through group policy (Group Policy, Password Settings/Account Restrictions/Profile Settings.

Daily check list of server (Event Logs, Memory utilization, disk space, Scheduled job Status Etc.)

Active Directory Services, Active Directory Group Policy Objects (GPO), Group Policy Management Console (GPMC), DHCP and DNS

Installation, Configuration, Administration and troubleshooting for VMware ESX servers. HA, DRS, VMotion and Troubleshooting of Virtual Center.

Creating and managing Virtual Machines, Installing VM Tools and allocating for end user.

Creating and managing VMware cluster. Enabling HA and DRS features in a cluster.

Strictly following ITIL (IT Infrastructure Library) procedure to resolve incidents.

Projects

Predicting if an SMS is a spam or not August 2017 – December 2017

Language: Python

Build statistical models using historical data to predict if the SMS is spam or not.

Performed data transformations, data cleansing using libraries in python.

Used Naïve Bayes and Support Vector Machine classifier for predicting whether a message is a Spam or not.

Text-based Analysis done on each message.

Phishing Website Detection August 2017 – December 2017

Language: Python

Developed pipelines to analyze large simulation datasets using Python libraries like NumPy, Scikit-learn, Pandas etc.

Architected and implemented analytics and visualization components for device data analysis platform to predict if a website is malicious.

Applied classification model to URL that a person is redirected to predict if the website is malicious or not.

Extra-Curricular Activities

Completed Machine Learning course on Udemy.

Completed Data Scientist course on DataCamp.

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