Data Science High School

Nikhil Gupta

*** *********** ***, *******, ** 510-***-**** **********@********.*** LinkedIn

EDUCATION

University of California, Berkeley, CA May 2025

Bachelor of Arts, Data Science with domain emphasis in Business/Industrial Analytics

• Coursework: The Structure and Interpretation of Computer Programs, Data Structures, Linear Algebra and Differential Equations, Foundations of Data Science, Introduction to Economics, Calculus, Principles and Techniques of Data Science, Concepts of Probability, Data Mining and Analytics, Human Contexts and Ethics of Data, Principles of Engineering Economics, Data Inference and Decisions, Econometrics, Introduction to Business Analytics, Entrepreneurship for All Tennyson High School, Hayward, CA May 2021

High School Diploma

WORK EXPERIENCE

Gateway Care and Rehab Center 2023 - Present

IT Support Technician & Receptionist Hayward, CA

• Troubleshot and repaired computers, phones, and other technology systems throughout the facility.

• Collected and analyzed data on hospital operations, patient demographics, and resource utilization, generating actionable insights to enhance efficiency, patient care, and overall hospital performance.

• Provided front-desk support by greeting visitors, answering phones, and assisting patients and staff with inquiries. Rishi Kumar Fellowship Program (Congressional Internship) 2022 Data Science Intern Saratoga, CA

• Applied data science principles using Python to optimize outreach efforts and maximize voter support for Rishi Kumar's congressional campaign in District 16.

• Segmented the voter database through detailed data analysis of demographics and past voting behavior, tailoring messaging and outreach strategies.

• Utilized predictive analytics to identify potential supporters and prioritize outreach efforts for efficient resource allocation.

• Examined voter interaction data to assess sentiment, concerns, and preferences, enabling real-time refinement of campaign messaging and strategies.

PROJECTS

2018 Primary Election Insights May 2024

• Conducted causal inference analysis to determine the impact of political endorsements on Democratic primary election success, controlling for demographic and campaign factors.

• Integrated and preprocessed election datasets from FiveThirtyEight and the Federal Election Commission, handling missing values, binarizing categorical features, and merging data sources.

• Built predictive models (Logistic Regression, Decision Tree, Random Forest) to forecast election outcomes using demographic and financial data, optimizing model performance with cross-validation.

• Identified key predictors of election success, highlighting the influence of non-party political committee contributions and endorse- ments on primary outcomes.

• Proposed future improvements, including expanding the dataset to Republican candidates and incorporating media coverage data for enhanced predictive accuracy.

Predicting Popularity of News Articles Dec 2023

• Developed machine learning models to predict the popularity of news articles using the Online News Popularity dataset (39,644 articles, 61 attributes).

• Conducted exploratory data analysis (EDA) and feature engineering, including outlier removal, categorical encoding, and normalization to improve model performance.

• Implemented Multiclass Classification, Binary Classification, and Regression models (Random Forest, KNN, MLP, XGBoost, and Linear Regression) to predict article shares.

• Achieved strong results in Binary Classification, successfully identifying articles with low engagement (bottom 20%) to assist media companies in content filtering.

• Proposed future enhancements, including Natural Language Processing (NLP) for content analysis and author influence modeling to refine prediction accuracy.

SKILLS

• Languages: Java, Python, SQL, R, HTML

• Tools: IntelliJ, Visual Studios, Xcode, Microsoft Excel, Microsoft PowerPoint, Tableau, Microsoft Office

• Communication: English - Native, Punjabi - Native, Hindi - Native, Spanish - Limited

• Libraries: NumPy, Pandas, Seaborn, Matplotlib, Regex, SciKit, PyPlt, TensorFlow

• Web Technologies: Git, Jupyter, LaTex

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