Sita Robinson

About Me

My name is Sita Robinson. I am a Senior Data Science major at Drexel University with a minor in Computer Science. I am expected to graduate with my Bachelors degree in 2020.

I am the president of Drexel Women in Computing Society (WiCS). Previously I was treasurer of WiCS for two years. My last job was in a data science co-op (6 month internship) at ELAP Services in Chesterbrook, Pennsylvania. In the summer of 2017, I was a Software Engineering Intern at Comcast in Philadelphia. Some of my hobbies include programming, photography, playing the clarinet, playing Scrabble and traveling around the world. I am originally a Northern Virginia/Metro D.C. native.

Work Experience

Data Science Co-op at ELAP Services
September 24, 2018-March 20, 2019
Software Engineering Intern at Comcast
June 19, 2017-August 25, 2017


Intermediate: Python, HTML/CSS, Javascript, Firebase, Microsoft SQL, MySQL, Oracle SQL, MariaDB, Android Studio, Markdown, Jupyter Notebook, C++
Beginner: R, Node.js, ArcGIS (ArcMap, ArcGIS Online), LaTeX, Java, Unix, Tableau, JQuery Mobile, JQuery, Flask, Ruby on Rails

Relevant Coursework

INFO 212,213 Data Science Programming I, II (Python)
INFO 250 Information Visualization (Tableau,RawGraphs, VOSviewer)
INFO 332 Exploratory Data Analytics (R)
INFO 400 Data Science Projects (Python)
INFO 440 Social Media Data Analysis (Python)
INFO 371 Data Mining Applications (Weka, RapidMiner)
STAT 201,202 Business Statistics
CS 171,172 Computer Programming I,II (C++)
CS 275 (Now: CS 375) Web and Mobile App Development (HTML, Javascript, NodeJS, AJAX, MySQL)
CS 260 Data Structures
CS 265 Advanced Programming Tools and Techniques
CS 283 Systems Programming (C)
SE 310 Software Architecture I (Java, Software Design Patterns)


Toast-Ongoing Senior Design Project

Toast is an automated financial planning application for financial advisors and their clients. The application will be developed using Django and ReactJS.

Credit Card Fraud Detection-Ongoing Personal Project

Using the Python Scikit-Learn library to train and test the dataset from Kaggle to predict whether a transaction is fradulent or not using classification algorithms.

Malaria Detection-Personal Project

Used a CNN model to classify images as being parasitized or not. Leveraged the library and Python.

Fashion MNIST Clothing Classification-Personal Project

Used deep learning algorithms and techniques to classify clothing images. Built using Tensorflow, Keras and Python.

News Tweet Analysis

Performed natural language processing on Twitter feeds using the Tweepy streaming API, Python, NLTK, Beautiful Soup and MongoDB.

Mushroom Classification

Used the Python Scikit-Learn library to train and test the "Mushroom Classification" dataset from Kaggle to predict whether a mushroom is poisonous or edible. Used classification algorithms including SVM, Naive Bayes, and Logistic Regression.

Food Production Analysis

Data pre-processing and exploratory data analysis on the "Who eats the food we grow?" dataset from Kaggle.

Quali-Personal Project

Developed a web application with backend to match the skills and qualifications needed for a job. Created a web scraper using the Beautiful Soup library in Python to scrape job data from Leveraged text analytics to match employee skills to job postings. Used Flask which is a framework to run Python as a web server.

Student Performance Analysis-Personal Project

Built machine learning models using random forest to predict what factors are most important for student performance in exams using the "Student Performance in Exams" dataset from Kaggle. Performed pre-processing and exploratory data analysis. This project was completed using the R language.

Graduate Admissions Analysis-Personal Project

Built a machine learning model using the linear regression, random forest, and gradient boosting algorithms to analyze what factors are most important for graduate admissions. The model was generated using the "Graduate Admissions 2" dataset from Kaggle. This project was completed using R.


A web app that allows people to make their own checklists and share with other members. Uses HTML, Javascript, JQuery Mobile, Bootstrap, MySQL, and NodeJS.

NOVA Datascience Signin and Attendee Randomizer-Personal Project

A web app for the NOVA DataScience Meetup Group that includes a sign-in form and a randomizer for prizes. Uses Firebase which is a NoSQL Database along with HTML and Javascript.

BuddyU App

An android social app for Drexel University students to collaborate on their schedules with the goal of making class time more efficient, collaborative, and fun. Made using Firebase and Android Studio.

Black Friday Analysis

Performed exploratory analysis of Black Friday data. In addition, used matrix factorization to study consumer behavior and provide recommendations for potential customers. We also explored the process of vectorization and the process of creating embeddings, using the results to find similar customers, find consumer groups using clustering, and predict what a given customer will buy.

Places I've Traveled

My Photos

Ⓒ Sita Robinson 2017