Currently an Extern @Amazon
Erronn Bridgewater
As a motivated NYU sophomore, I’m honing my expertise in business technology and data analytics, eager to embrace new challenges and make an impact.
Work samples
Dive into my portfolio showcasing relevant projects and skills in operational strategy, AI, and data analytics.
Amazon · Jul 2026 · ✅ Verified by Extern
Amazon Operational Strategy & People Analytics Externship
Imagine shaping how AMAZON — yes, THE Amazon — welcomes and keeps its workforce. Every year, Amazon loses billions because new hires leave before Day 90. You’re going to fix that. In this externship, you’ll web scrape real-world employee reviews from across the web, extract actionable insights, and
Data AnalysisPythonStrategyOperationsPython ScrapingGoogle ColabClaudeConsultingAI4ALL Ignite
Direct end-to-end engineering project strategy for a cross-functional technical team, translating raw data into actionable insights through quantitative modeling and structured analysis (Pandas, Matplotlib).
PandasMatplotlibCodepath · May 2026
PawPal+
PawPal+ is an intelligent Python assistant that manages feeding, walking, and grooming for multiple pets. It uses an agentic workflow to prioritize tasks by considering pet health, owner energy, and time constraints, with a Streamlit-based interface.
AI Agent DevelopmentAI-Enhanced DesignAPI IntegrationBack-end DevelopmentClaudeGithub CopilotAI EngineeringPrompt EngineeringPythonStreamlitNYU Rouge Aerospace · Apr 2025
NYU Rouge Aerospace Flight Simulation
Brookhaven National Laboratory · Aug 2023
Performance Study and Optimization of Low-Gain Avalanche Diodoes
This project was about calibrating Negative Temperature Coefficient thermistors across a wide temperature range (-60°C to 180°C) to modify Low Gain Avalanche Diode sensors for durability in extreme space temperature conditions.
Data VisualizationData ScrapingBack-end DevelopmentData AnalyticsData SciencePandasPresentation SkillsQuantitative Analysis
About me
As a motivated NYU sophomore, I’m honing my expertise in business technology and data analytics, eager to embrace new challenges and make an impact.
I’m Erronn Bridgewater, a sophomore at New York University pursuing a Bachelor's in Business and Technology Management. With experience in operational strategy and people analytics, I’m passionate about leveraging data to drive impactful business decisions.
Externships
Amazon Operational Strategy & People Analytics Externship
Amazon
Experience
Operational Stragey & People Analytics Extern
Amazon (Extern) · May 2026 - Jul 2026
Operations Analyst
NYU Rouge Aerospace · Apr 2026
AI Fellow
Handshake · Dec 2025
NYU Admissions Ambassador
New York University · Nov 2024 - Sep 2025
Academic Peer Leader
New York University · May 2025 - Aug 2025
Mission Finance & Risk Analyst
NASA L'SPACE Mission Concept Academy · May 2025 - Aug 2025
Flight Sim Developer
NYU Rouge Aerospace · Apr 2025
Education
New York University
B.S. in Business and Technology Management · Class of 2028
Skills
✅ Verified by Extern
Amazon Operational Strategy & People Analytics Externship
Imagine shaping how AMAZON — yes, THE Amazon — welcomes and keeps its workforce. Every year, Amazon loses billions because new hires leave before Day 90. You’re going to fix that. In this externship, you’ll web scrape real-world employee reviews from across the web, extract actionable insights, and
Overview
In my externship with Amazon, I focused on enhancing employee retention strategies by analyzing workforce data. I conducted web scraping of employee reviews to gather insights and developed persona-driven strategies aimed at improving the onboarding experience. This project was dedicated to understanding how data can inform better decision-making in workforce management.
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What I've accomplished
I produced an attrition analysis and briefing note, visualized keyword and sentiment patterns from Glassdoor and YouTube reviews, built a cohort friction map that prioritized Full-Time Associates, and documented root causes linked to HR and operational factors.
Project breakdown
AI4ALL Ignite
Direct end-to-end engineering project strategy for a cross-functional technical team, translating raw data into actionable insights through quantitative modeling and structured analysis (Pandas, Matplotlib).
Codepath · May 2026
PawPal+
PawPal+ is an intelligent Python assistant that manages feeding, walking, and grooming for multiple pets. It uses an agentic workflow to prioritize tasks by considering pet health, owner energy, and time constraints, with a Streamlit-based interface.
Overview
PawPal+ is an intelligent Python assistant that manages feeding, walking, and grooming for multiple pets. It uses an agentic workflow to prioritize tasks by considering pet health, owner energy, and time constraints, with a Streamlit-based interface.
What I've accomplished
Archiecture Overview: Human Input: Users define pets, owners, and specific care tasks via the Streamlit UI. The Scheduler: Acts as the central orchestrator, holding the state of the task queue. AIAgent (Gemini): The Scheduler sends the context to the AI Agent (powered by Gemini 2.5 Flash), which "reasons" through priorities. Validation & Refinement: The system programmatically checks the AI's plan against hard constraints, like the owner's total time budget, and refines the list if necessary.
NYU Rouge Aerospace · Apr 2025
NYU Rouge Aerospace Flight Simulation
Brookhaven National Laboratory · Aug 2023
Performance Study and Optimization of Low-Gain Avalanche Diodoes
This project was about calibrating Negative Temperature Coefficient thermistors across a wide temperature range (-60°C to 180°C) to modify Low Gain Avalanche Diode sensors for durability in extreme space temperature conditions.
Overview
This project was about calibrating Negative Temperature Coefficient thermistors across a wide temperature range (-60°C to 180°C) to modify Low Gain Avalanche Diode sensors for durability in extreme space temperature conditions.
What I've accomplished
• Achieved ±2°C sensor calibration accuracy and improved durability across (−60°C to 180°C), utilizing Matplotlib, SciPy, NumPy, and Pandas for statistical analysis. • Automated data collection of∼60 temperature-resistance measurements, reducing experiment time∼60% by using an Arudino-based data acquisiton system.