Ayush Majumdar

نبذة عني

BS in Data Science Major @ University of California, Davis | Target Graduation: June, 2025

Relevant Coursework: Statistical Data Science (I, II, III), Data and Computing, Data Structures, Linear Regression, ML, Excel

E…

BS in Data Science Major @ University of California, Davis | Target Graduation: June, 2025

Relevant Coursework: Statistical Data Science (I, II, III), Data and Computing, Data Structures, Linear Regression, ML, Excel

EXPERIENCE AND LEADERSHIP
DATA ENGINEERING INTERN (MOBILE APP DEVELOPMENT) @ ALBERTSONS CO., Pleasanton, CA
SWE Intern
Worked with PowerBI, Kotlin, and Android Studio for AcuPick (eCom Picking app) and Safeway Applications.

JUN’23 - SEP’23

Analyzed picking data using PowerBI, and returned efficient strategies and possibilities to implement efficient service.
Data Analyzed potential benefits and issues with integrating Twilio into Albertson’s Systems.

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● Worked back-end on mobile development with accurate delivery picking software for retail.
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Focused on Two-Way Communication between customers and pickers, e.g. calling and texting software with Twilio.

PROJECT LEAD FOR DAVIS DATA SCIENCE., Davis, CA
Project Lead
UC Davis Department Club focused on Data Science and exploring extensive AI and ML related topics.
Leading a group of eight students on a search engineering optimization project.
Cleansing data using Scrapy, BeautifulSoup, manual removal, and utilized TensorFlow to optimize deep learning in search engines.
Used Tableau in order to find quantitative correlations in search engine usage.

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JAN’24 - CURRENT

AI/MACHINE LEARNING LEAD DEVELOPER FOR AGGIE SPORTS ANALYTICS, UC Davis
AI/ML Lead Developer
UC Davis-based organization that uses AI/ML to analyze trends and build tools/models for public access and prediction usage.

OCT’23 - CURRENT

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Integrated OpenCV, Python (Pandas/Numpy/SciKit), and localized data.
Lead Developer on a four person development team to build a project that takes the two-minute report from NBA games to analyze
trends in referees, affected games, and false calls to create models to predict future games.

TECH ASSOCIATE @ GOOGLE DEVELOPER STUDENT CLUB
App Development Technical Associate
Google Developer Student Club fosters student engagement in technology through collaborative projects and activities.

OCT’23 - CURRENT

Leading a group of five students on app development projects, employing software such as React Native and Android Studio.

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● Managing and scheduling meetings to instruct and guide students through app development projects.

MACHINE LEARNING, AI, AND DATA MODELING PROJECTS
CLUTCHCALLS REFEREE SPORTS BETTING MODEL TRAINING AND APPLICATION. 4 hrs per week. 10 wks.

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Cleansed and organized the NBA’s two-minute report dataset utilizing Pandas to best-fit project needs.
Trained a model with SKLearn to consider numerous hyperparameters to form accurate predictions for individual referees’
correct/incorrect calls per game between specific teams.
Utilized predictions using a neural network to form lines as over-under betting values for gamblers to bet on, ensuring maximum
potential profit for app creators, while balancing out with maximum potential market usage.
Intend to publish API to potentially outreach to companies, i.e., PrizePicks, and DraftKing.

RESUMESCORE.AI. 3 hrs per week. 3 wks.

● Web scraped and vectorized data and job postings from Indeed.com utilizing beautifulsoup and NLP; matched it with vectorized

resumes to suggest the highest compatibilities for resumes.
Data-scraped data from Indeed using Selenium to get rid of stopwords, and verify the data.
Utilized MongoDB to increase efficiency and designed the front end of the WebPage, using React, NodeJS, and JS (JavaScript).

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LIFE EXPECTANCY PREDICTION REGRESSION ANALYSIS AND MODEL. 6 hrs per week. 3 wks.

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Utilized R with packages such as "MASS," "car," "leaps," and "psych" for data analysis.
Conducted residual analysis and variable transformation to enhance model performance.
Utilized correlation matrix and VIF to identify and address multicollinearity concerns, and stepwise regression for variable selection.
Conducted various diagnostic checks, including residual histogram, QQ plot, confirming model linearity and homoscedasticity.

CONTAGION CLASSIFICATION MODELING TOOL. 8 hrs per wk. 2 wks.

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Utilized SKlearn, NumPy, MatPlotLib, and Pandas on Jupyter to analyze a breast cancer dataset.
Used Tenserflow ~ Keras for deep learning analysis of data.

CERTIFICATIONS
TIM BUCHALKA PYTHON MASTERCLASS CERTIFICATION. 4.0 hours per week. 17 wks.

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Acquired pre-requisite Python skills to move into specific branches - Machine Learning, and Data Science.
Understand both Python 2 and Python 3, and understanding of Python to apply for Python-based jobs confidently.

Technical Skills: Python (Pandas, Numpy, matplotlib), R, Data Processing and Cleansing | Tableau, PowerBI | Web Scraping
(BeautifulSoup, Selenium), Keras | SQL, Excel | Java (Kotlin), JavaScript, Android Studio, Twilio Voice Android SDK, Git |
Interests: Basketball, Cricket, Guitar, Weight Lifting, Amusement Parks

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