I'm a graduate student at University of Illinois Urbana-Champaign, pursuing MS Information Management in a Data Science track. Being from a computer science background, I've spent years experimenting with data, algorithms and computational capabilities. While I've worked with a Fortune 500 clientile solving real world problems using data science, I'm also an avid research enthusiast, exploring computational creativity extensively in the domain of natural language processing.
Visualization and dashboards using Python, R, Tableau and PowerBI
Data deduplication, root cause/trend analysis, customer segmentation, market basket analysis, recommendation systems.
Data wrangling to maintain and retrieve data from structured and unstructured databases using advanced queries and query automation.
Statistics, probability, time series analysis, predictive modeling, model training and fine-tuning.
Text classification, summarization, question- answering, named entity recognition, automatic speech recognition.
Quantitative analysis, monitoring key performance indicators, dashboards, reports, business resource documents.
MS Information Management, Data Science & Analytics specialization
August 2022 - May 2024
CGPA - 4.0/4.0
BS Computer Science
August 2017 - June 2021
CGPA - 3.7/4.0
1+ years of experience in data science, analytics and business intelligence.
Graduate Research Assistant | Aug 2022 - Present
Data Analyst (Consulting) | Oct 2021 - July 2022
Research Intern | Jan 2021 - July 2021
Business Analyst Intern | July 2020 - Sept 2020
Data Science Intern | July 2019 - Sept 2019
Scroll right! View my data analytics, machine learning and natural language processing projects and publications.
A simple content-based music recommender which takes input of artist name or song name from user, and recommends similar songs.
Optimized prediction rates of ML and neural network classifiers for text classification of Nepal earthquake microblog data using term weighted scheme to attain 97% accuracy.
Implemented a classifier in Python to predict the probability of default of loan applicants based on credit history data using statistical analyses, visualizations and machine learning algorithms such as Logistic Regression, Random Forest and XGBoost.
Experiments with stable diffusion via HuggingFace models, generated digital art using textual prompts.
Built a news summarizer tool using HuggingFace Facebook BART Large CNN model which allows users to input any type of news article and summarizes it into a concise paragraph of custom range output.
Designed an e-commerce dashboard in Tableau to enable tracking of campaign-specific performance metrics such as customer churn rate, cost per lead, return on investment, email open rate and conversion rate for digital marketing campaigns.
Designed a delinquency tracker using Tableau to monitor delinquency amounts, days passed due, months on book and risk segments for 100K+ customers of multiple loan portfolios to facilitate strategy management.
Built a people analytics dashboard in PowerBI to monitor employment distribution and job attrition rate across various job roles as per key performance indicators such as gender, department and experience of employees using survey data.