Leads data-driven decision-making by applying ML techniques; leverages communication skills to promote multi-practice teamwork.
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Experience
Grader and Tutor, Rutgers University 09/2019 – 12/2019
• Evaluating assignments and exams for data analysis and data visualization course in R, SQL and Tableau.
• Tutoring for Management Information Systems, Business Relationship Management, Production & Operation Management.
• Prepare and facilitate tutoring workshops, collaborative projects, or academic support sessions for small groups of students.
• Review class material with students by discussing text, working solutions to problems, or reviewing worksheets and assignments
Assistant Analyst Intern, Vora Trading Co. 05/2017 – 07/2017
Tracked financial data and evaluated favorable inventory expenses as company’s first-ever intern.
• Advanced 6% (~$12k) cost savings by suggesting optimal inventory purchasing and price skimming strategies.
• Identified sales KPIs and trends by inputting and processing 10+ years of paperwork data in SQL database for a wide variety of
applications and business uses. Designing databases on MS SQL server and ensuring their stability, reliability, and performance.
• Writing SQL queries to store, sort and retrieve data, handling missing data and fix any issues related to database performance
and provide corrective measures.
• Presented visualizations using Microsoft Excel and creating dashboards using VLOOKUP and pivot tables.
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Projects
Customer Segmentation Analysis (Grade: A) – Achieved 96% accuracy while providing customer segment insights of a car company;
developed metrics and created visualizations using R. Created a confusion matrix to compare performance of classifiers including
decision tree, random forest, linear regression, KNN, SVM, and Naive Bayes.
• Coordinated weekly meetings, assignments, and work schedules of 4 peers as Project Lead.
Global Weather Prediction (Grade: A) – Attained 92% accuracy while forecasting global weather for the next 3 years based on past
20-year data using R. Compared accuracy of seasonal naive, exponential smoothing, Holt-Winters, ARIMA, and time series linear
models by calculating the mean absolute error.
• Ensured data accuracy by conducting preprocessing. Resolved weekly issues and assigned tasks among 3 peers.
Vehicle Theft Detection (Grade: A) – Obtained 89% accuracy while performing face recognition using Haar Cascade, LBPH, and PCA.
Created a threat alert system and designed a web page for automated notification. Tools Used: Python, HTML, CSS, Raspberry Pi.
• Project stood first in class and was recognized by multiple company executives in Prakalpa 2018 State-Level Competition.
Hotel Web Application (Grade: A) – Provided insights on customer handling by developing a web application to acquire and
categorize client data in 4-member team. Designed ERDs, created database constraints, and established front- and backend
connection. Tools Used: Python CGI, SQL, MySQL Workbench, HTML, CSS, Bootstrap, Apache HTTP Server.
Tweet Sentiment Analysis (Grade: A) – Deduced trends in subjectivity and polarity of tweets by performing web scraping and
sentimental analysis on live Twitter data using Python, TextBlob, and Twitter API, BeautifulSoup.