Data Social Media

Marzieh Mirzaeibonehkhater

****************@*****.*** 317-***-**** linkedin.com/in/MarzieMirzaei

Core Qualification

Relational and NoSQL database design

and development

High dimensional data analysis to

produce actionable insights

Implemented K-means clustering for

clustering users in social media

Applied SVM classification with

different kernels for text categorization

Implemented bag of word model

Matrix Factorization model to predict

user’s rating to the items

Technical skills

Programming Stack: Python, Java,

JavaScript

Databases: MySQL, MongoDB

JavaScript Stack: jQuery

Web Technologies: HTML5,CSS3

Framework: Django, Hadoop

IDE: Spyder, IntelliJ, NetBeans,

Eclipse

Operating Systems: Windows

Map reduce programming model,

HDFS

Activities

Poster Presentation- 2nd Annual

Engineering and Technology

Leadership Symposium

Led a team of 6 researchers-

Develop a recommendation system for

the CourseNetworking network-2016

Coding Competition- Hacker Rank

Achievements

The Semi-finalist in Data Incubator

Fellowship: October 2017

Jafari’s Fellowship Award: August

2015-August 2016

ECE Department scholarship: August

2016-present

Certificate of MATLAB-IEEE 2014

Objective

To obtain a data scientist position to identify and solve business and technical challenges processing dirty and unstructured data that utilizes my technical expertise and team management skills to develop cognitive and scalable software

Education

Master of Science in Electrical and Computer Engineering (May 2018) Purdue School of Engineering and Technology, IUPUI

Bachelor of Science in Electrical Engineering (Dec 2013) Shiraz University of Technology

Relevant courses

Advance database

Artificial Intelligent

Recommendation systems

Algorithm design and analysis

Machine Learning

Deep Learning - Neural Networks

Experience

CourseNetworking(CN): Principle software researcher (August 2015-Present) Designed and implementing a hybrid recommender system for personalizing news feeds based on users preferences by using machine learning technique and considering user interaction and textual information

Data parsing: Analyzed unstructured data contains data for 6k users and 11k items in JSON format to make meaningful data-like contributions to the production code and provide basic insights and analyses, and brought the relevant data into a central system

Feature extraction: Developed supervised machine learning using Support Vector Machine(SVM) with Gaussian and different kernels and test other supervised techniques like logistic regression to classify user-generated content

Sentiment analysis (SA): Applied SA for computational analysis of user’s opinion and attitudes toward posts in the CN network

Clustering method: Developed clustering technique to exploited relationship between users using data from CN network to cluster the top nearest neighbors of each individual user purely according to the user’s interaction.

Evaluation: Performed and applied matrix factorization model finding 85 % accuracy to predict the news feeds to the users based on their interests. Developed application performed better than the traditional Collaborative Filtering (CF) algorithm Sandwich Ordering System (October 2017)

Designed and modeled a sandwich ordering system by using an object oriented modeling using JAVA language to simulate real life of a Software team

Implemented the system allows the customers to order from a list of signature sandwiches and custom sandwiches with at least a Bread and a main filling, and an option to order Drink along with Sandwiches

Created the system to allow the user to make multiple orders, and optionally the user could add cheese, vegetables and condiments

Build the system to present the user with total price before placing the final order Web application to visualize traffic incidents (January 2017 – May 2017) Designed scalable web application architecture using message queuing service to track road traffic incidents

Developed backend micro services using Django and MySQL

Collaboratively utilized the application frontend using Bootstrap3,HTML5 and jQuery

Utilized MongoDB based search engine to get search functionality over social media posts using inverted index algorithm

Created micro service for data extraction using twitter API’s

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