I am an Information Management professional, passionate about telling stories backed up by data. My goal is to combine my technical and business skills to reach smarter business decisions. I am currently researching on fake news early detection using machine learning. After securing my master's degree I plan to use my knowledge in data science to generate actionable insights for companies.
Working under the supervision of Oren Shklarsky, Senior Data Scientist at Postmates.
Building a personalized recommendation system and user interface, to recognize healthy and unhealthy food products for users from their genome data and by analyzing nutrients in different food products to reduce the risk of catching a disease
Combining data from various sources to detect traits like lactose & gluten & classifying food products as healthy/unhealthy
Conducting research under Dr. Reza Zafarani on fake news early detection by using machine learning on news content of two-real world datasets
Exploring fake news characteristics at lexicon-level, syntax-level, semantic-level & discourse-level enabling interpretability
Outperforming current content/propagation-based models and comparable to hybrid models based on experimental results
Researching with Professor Jeffrey Saltz on metrics for tracking work of a data analytics team using agile methodology
Building & testing an environment to enable collaboration of a data science team with distribution and monitoring of tasks
Improved reporting efficiency by building dynamic graphs using Neo4j which resulted in savings of over $10k in expenses
Improved marketing effectiveness by analyzing sales performance, customer engagement & marketing expenditure datasets
Created pipelines to automate data cleaning process resulting in a 35% reduction in the time required to perform these steps
Enforced master data management principles to create project workflow & carry out various data cleaning & munging steps
Coordinated with the internal and offshore team to create deliverables and facilitate project progress and product development
Performed data analysis on healthcare data to derive quantitative & qualitative insights which improved the marketing effort of the client
Developed front end of iOS application, for ecommerce, from scratch which accounted for 30% of sales for the company
Created automated personalized notifications for customers from past behavior & increased notification click rate by 15%
Instituted user action analysis to interpret user patterns for targeted marketing, increasing engagement with app by 10%
You can interact with the project here - Application
• Implementing a machine learning solution to predict the gender of a user using their user profile and some of their tweetsGPA: 3.95/4
GPA: 7.33/10
Relevant Coursework: Data Structures, Software Engineering, Object Oriented Programming, Computer Architecture, Soft Computing