JOSEPH CHANIN
jchanin3@gatech.edu | www.linkedin.com/in/joseph-chanin
GEORGIA INSTITUTE OF TECHNOLOGY
December 2021
GPA: 3.69
Graduated with highest honors from the H. Milton Stewart School of Industrial & Systems Engineering (ISyE) with my Bachelor of Science degree in ISyE, concentrating in Analytics & Data Science.
Honors/Awards: Dean's List, Zell Miller Scholarship Recipient
Organizations: Undergraduate Consulting Club, Engineers Without Borders, Alpha Epsilon Pi Fraternity, Hillel, Chabad
ALAN C. POPE HIGH SCHOOL
May 2017
GPA: 4.72
Valedictorian of the Pope High School Class of 2017.
Honors/Awards: Daughters of the American Revolution Fielding Lewis Chapter Citizenship Award, National Merit Scholarship Commended Student, and AP Scholar with Distinction
GEORGIA TECH SCHOOL OF CITY & REGIONAL PLANNING
RESEARCH ASSISTANT
Sep 2022 - Feb 2023
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Writing web scrapers using Python packages pyautogui, pytesseract, pandas, and numpy to efficiently collect information from 3,000,000+ datapoint in the GA Secretary of State's business registration database, supporting a project of the University System of Georgia to better understand the effects of the HOPE scholarship on propensity to pursue entrepreneurship.
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Writing web scrapers using Python packages Selenium and BeautifulSoup to efficiently collect LinkedIn profile information for 1,000,000+ alumni of public universities in Georgia
GEORGIA TECH ISYE SENIOR DESIGN PROGRAM —
THE COCA-COLA COMPANY
Feb 2021 - Dec 2021
Along with a team of six other GT ISyE students, collaborated with senior supply chain managers at Coca-Cola to redesign their chilled distribution network for the Fairlife and Simply brands to minimize network cost
Formulated a mixed integer quadratic program (MIQP) in Gurobi python that is expected to reduce network costs by 25% for potential savings of $5.2 million/year, and packaged into an intuitive GUI that illustrates the 2-year integration plan.
Selected as one of three finalists from among 23 ISyE teams, evaluated on methodology, value, and professionalism.
Learn more about this project here
NISSAN MOTOR CORPORATION
VEHICLE QUALITY ENGINEERING INTERN
May 2021 - August 2021
Developed and implemented automated quality systems to monitor new model vehicle key control characteristics, saving each end user an estimated 4 hours/week in data collection, data analysis, and report generation
Leveraged database systems technology to build a cohesive data storage system that allows vehicle data results to be analyzed and compared in real time with historical control factor data in order to quantify labor efficiencies
Constructed data visualization dashboards in Tableau to efficiently present payback periods for investments
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GEORGIA TECH UNDERGRADUATE CONSULTING CLUB
STUDENT CONSULTANT
Jan 2020 - Feb 2021
UPS — Team Lead
Performed market research and statistical analyses in Microsoft Excel in order to identify driving factors behind successful internships to help UPS Global Customer Solutions more efficiently and confidently select top candidates
Leveraged Tableau to construct 7 easily digestible dashboards with a user-friendly interface that dynamically integrated our findings with UPS recruiting data
Managed a team of 5 and served as the key liaison for direct client communication with UPS to prioritize project scope, timeline, and deliverables
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Advocate — Senior Analyst
Developed 5 dynamic dashboards utilizing Microsoft Power BI based on data stored in Advocate’s data warehouse
Conducted market research and industry benchmarking to determine KPIs to display on dashboards that will be regularly used by 40 Advocate employees across multiple departments
Learn more about this project here
CS4641 MACHINE LEARNING
TEAM PROJECT, "PREDICTING AMERICAN FOOTBALL PLAYS"
January 2021 - May 2021
Implemented and tuned a Neural Network in Keras consisting of two hidden layers and a variety of sigmoid and soft-max activation layers with an Adam optimizer using a 0.01 learning rate to predict offensive plays in American football with 80.25% accuracy
Cleaned dataset, conducted Principal Component Analysis to remove unnecessary features, evaluated performance of Random Forest and Multi-layer Perceptron models in sklearn, and used Synthetic Minority Oversampling Technique to balance minority classes in the dataset
Learn more about this project here
Skills: Python (5 years), SQL (2 years), R (2 years), Tableau (2 years), Java (1 year), Microsoft Power BI (1 year), NumPy, Pandas, Gurobi Optimization, Keras, Google Distance Matrix API, Simio, Microsoft Excel, Probability/Statistics, Regression/Forecasting