I am a graduate student from University of Illinois at Urbana-Champaign with major in Industrial Engineering. I specialize in Data Analytics. I have more than a year of experience as Data Analyst.
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Experience
Technical skills: Python, R, SQL, Matlab, Excel, SAS, Git, Tableau, Google Data Studio, PowerBI, Google Cloud, BigQuery, APIs
Functional skills: Verbal Communication Skills, Leadership, Management, Problem-solving, Time management, Data Mining, Data Cleaning & Manipulation, Data Management, Data Modeling, Data Visualization, ETL, Teamwork
Certifications: Applied Data Science in Python Specialization, SAS Programmer Specialization, Bayesian Statistics from Concepts to Data Analytics with Honors, Databases and SQL for Data Science, R Programming, Programming Foundations: Data Structures
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GRAYBAR ELECTRIC COMPANY INC.
Champaign, IL
Lead Data Analyst Intern Dec 2019 - Present
• Automated collection of 25000+ product pricing from competitors on Google Cloud to web scraping data to run every week by using Compute Engine and Google Scheduler
• Devised a model to scrape data by parallel processing using threading and queuing decreasing the time taken by 75% and validated data sets with statistical tools and analysis
• Deployed interactive reporting with Tableau based on specification of end user for analytical assessment of data for faster decision making and price analysis of products
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GRAYBAR ELECTRIC COMPANY INC. Champaign, IL
Data Analyst Intern May 2019 - Dec 2019
• Directed team of 3 to develop mapping visualization tool by utilizing Google Map APIs that allowed warehouse executives to compare normal vs optimized routes for better assessment of route optimization algorithms
• Product Development - Engineered prototype to provide strategic direction for scenario planning of various branches in Graybar using a stratification model based on productivity and profitability
• Delivered presentations to an audience of 25+ to demonstrate the prototype which had an impact on staffing across Graybar branches
• Automated data gathering and cleaning process of complex datasets extracted from HANA database for data analysis and increased the data quality by 13% by using Pandas package
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ILLINOIS GEOMETRY LAB Champaign, IL
Lead Data Analyst Jan 2019 - May 2019
• Headed team of 4 to collaborate with Healthcare Department of Urbana-Champaign and delivered presentations on predicting inspection scores of restaurants from data collected for over 19000 restaurants in Champaign county
• Implemented predictive models like linear regression and 2-layered Neural Network algorithms for inspection score prediction with mean square error of 14.93 and 6.79 respectively
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Projects
Image Ranking
• Designed Deep Ranking model for computer vision similar to Google Image Search Engine to characterize fine-grained images based on likeliness
• Employed ResNet architecture to achieve an accuracy of 61.2% on Tiny Image dataset using PyTorch package
=======================================================Sentiment Analysis of Patients’ records
• Created Python script using Regex package for cleaning patient feedback records to create vector representation using word embedding Word2Vec
• Implemented Bag of Words model using PyTorch package to predict sentiments and thereby achieving an accuracy of 90.82%
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Big Mart Sales Forecasting
• Built a predictive model for forecasting Big Mart Sales by implementing Machine Learning methods like Lasso and Ridge Linear Regression and Random Forest using Scikit-Learn package
• The metrics comparison concluded that Random Forest method yielded better prediction with an accuracy of 62.13%