Peter Mangoro profile picture

Hey, I'm Peter Mangoro Data Analytics Student

I build robust backend solutions and extract actionable insights from data. Based in New York, combining 3+ years of software development experience with advanced analytics education at Yeshiva University.

About Me

As a Software Developer with 3+ years of experience transitioning to Data Analytics, I leverage my backend development expertise and analytical thinking to build robust solutions and extract meaningful insights. My approach combines technical implementation with data-driven analysis, helping organizations streamline workflows and make informed decisions.

Work Experience

Aug 2024 - Dec 2024

Software Developer at
Propertybook

Jan 2023 - Aug 2024

Software Developer at
SoliderMed

Featured Data Analytics Projects

Explore my recent work combining software development expertise with data-driven insights
AWS Serverless ETL Pipeline
AWSCloud ComputingETL

AWS Serverless ETL Pipeline

Dec 2025

AWSCloud Computing

Built a complete serverless ETL pipeline on AWS that processes e-commerce sales data from ingestion to visualization. Implemented automated data processing with AWS Glue, SQL analytics with Athena, and interactive dashboards with Nuxt 4 and QuickSight—all for less than $2/month.

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AWS Sentiment Analysis System
AWSCloud ComputingServerless

AWS Sentiment Analysis System

Sept 2025 - Oct 2025

AWSCloud Computing

Built a production-ready sentiment analysis system for customer feedback analysis using AWS Free Tier services. Implemented serverless architecture with Lambda, DynamoDB, S3, and API Gateway, creating a cost-effective solution that processes thousands of feedback items with 75-80% accuracy.

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Fraud Detection System
Machine LearningAnomaly DetectionFraud Prevention

Fraud Detection System

Aug 2025 - Sept 2025

Machine LearningAnomaly Detection

A comprehensive machine learning system for detecting fraudulent transactions in mobile money services using unsupervised anomaly detection. Implements Isolation Forest algorithm to identify potentially fraudulent transactions with ~2% accuracy rate.

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GymTracker Streamlit Dashboard
StreamlitData VisualizationFitness Analytics

GymTracker Streamlit Dashboard

July 2025 - Sept 2025

StreamlitData Visualization

Developed an interactive fitness tracking application using Streamlit and Python. Features include workout analytics, progress visualization, and personalized recommendations based on user data patterns.

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Hospital Readmission Prediction Model
RMachine LearningHealthcare Analytics

Hospital Readmission Prediction Model

Aug 2025 - December 2025

RMachine Learning

Built three machine learning models (Logistic Regression, CART, Random Forest) to predict 30-day hospital readmissions using data from 130 US hospitals. Achieved 60-62% accuracy with high interpretability, enabling healthcare providers to identify high-risk patients and improve care outcomes.

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Traffic Violation Data Analysis
Data AnalysisPythonJupyter Notebooks

Traffic Violation Data Analysis

Jan 2025 - June 2025

Data AnalysisPython

Conducted comprehensive analysis of traffic violation data using Jupyter Notebooks and Python. Identified patterns in violation types, locations, and time periods to help improve traffic safety and enforcement strategies.

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Latest Article

My insights on data analytics methodology and best practices

My First AWS Adventure: Building a Sentiment Analysis System on a Budget

From zero to production-ready: How I built a full-stack sentiment analysis platform entirely within AWS Free Tier, exploring serverless architecture, cost optimization, and creative problem-solving along the way.

Building a Serverless ETL Pipeline on AWS: From Raw Data to Interactive Dashboards

How I built a complete data analytics pipeline using AWS serverless services—processing CSV files, cleaning data, enabling SQL analytics, and serving insights through interactive dashboards—all for less than $2/month.

Predicting Hospital Readmissions: A Machine Learning Journey

How I built three ML models to predict 30-day readmissions in diabetes patients using Logistic Regression, CART, and Random Forest
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Let's Connect

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