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  • Clarkson University
  • New York

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Thooms-coder/README.md

Mutsa Mungoshi

I am an Applied Data Scientist and Data Engineer with a foundation in engineering, machine learning, and scalable data systems. I am currently pursuing an M.S. in Applied Data Science at Clarkson University (GPA: 4.0), where my work focuses on building reliable data pipelines, production-ready analytical systems, and decision-support tools for research, operations, and policy.

My background combines:

  • Engineering-driven problem solving
  • End-to-end data system design (OLTP → ETL → analytics)
  • Statistical modeling and machine learning
  • Translating complex datasets into actionable insight

Technical Focus

  • Data Engineering: SQL, data warehousing, star schemas, SCD Type 2, ETL/ELT pipelines, incremental fact loads
  • Analytics & Machine Learning: Python, R, regression, PCA, clustering, classification, feature engineering
  • Visualization & Reporting: Tableau, Plotly, Shiny, interactive dashboards
  • Applications: Flask, SQLAlchemy, REST-style backends, full CRUD systems
  • Tools & Platforms: Git, MySQL, Snowflake, Docker, AWS (EC2, S3, Lambda), Airflow

Selected Projects

ZAGI Data Warehouse

SQL | Data Engineering
End-to-end OLTP → staging → data warehouse implementation for a retail and rental business. Designed dimensional models with SCD Type 2 handling, intermediate fact tables, incremental and late-arriving fact loads, analytical aggregates, and automated ETL validation.

https://github.com/Thooms-coder/zagi-data-warehouse

Multimodal Taxi Data Analysis

Python | Big Data | ETL | Visualization
Large-scale analysis of urban traffic using image and audio data. Built reproducible ETL pipelines and cross-modal validation workflows to detect anomalies and data quality issues across heterogeneous data sources.

https://github.com/Thooms-coder/multimodal-taxi-data-analysis-big-data

SNAP Participation and Structural Cost Analysis

R | Statistical Analysis | Policy Analytics
Research-driven analysis of 3,142 U.S. counties examining how SNAP participation relates to structural cost-of-living burdens. Applied PCA, regression, and clustering to uncover regional cost patterns and policy-relevant insights.

https://github.com/Thooms-coder/snap-participation-and-structural-cost-analysis

Shibui Productivity Planner

Python | Flask | Full-Stack Application
Designed and built a full-stack productivity and wellness planning platform with user authentication, task tracking, balance scoring, and a relational SQL backend supporting multi-user workflows.

https://github.com/Thooms-coder/shibui-work-wellness-planner

Material Selector Dashboard

R | Shiny | Decision Support
Interactive Shiny application enabling engineering teams to compare materials by cost, strength, and sustainability using Ashby-style plots, radar charts, and dynamic filtering.

https://github.com/Thooms-coder/material_selector_shinyApp

Metro Status Prediction Pipeline

Python | Machine Learning
Machine learning pipeline predicting U.S. metro status using engineered cost-of-living features and multiple classification models, with an emphasis on interpretability and feature structure.

https://github.com/Thooms-coder/metro-status-prediction-pipeline

Applied Experience

  • Research Assistant – Data Analysis (Clarkson University):
    Analyzed 50,000+ time-series records from wastewater treatment systems, built regression and time-series models, and developed interactive visual analytics to guide operational decisions.

  • Software Developer & Database Assistant (Clarkson University):
    Engineered a SQL-backed system for a 200-member rowing club, designing relational schemas and ETL pipelines that automated reporting and reduced manual effort.

Contact

I am interested in roles and collaborations involving data engineering, applied machine learning, analytics systems, and research-driven data work.

Pinned Loading

  1. multimodal-taxi-data-analysis-big-data multimodal-taxi-data-analysis-big-data Public

    IA626 Big Data project analyzing multimodal urban traffic data (image and audio) through reproducible ETL pipelines and cross-modal visual analytics to detect anomalies and data quality issues.

    Python

  2. zagi-data-warehouse zagi-data-warehouse Public

    End-to-end OLTP to data warehouse implementation with SCD Type 2 dimensions, incremental ETL, and analytical aggregates.

    SQL

  3. snap-participation-and-structural-cost-analysis snap-participation-and-structural-cost-analysis Public

    This project analyzes how SNAP participation rates relate to structural cost-of-living patterns across U.S. counties. Using PCA, regression, and clustering on county-level cost shares, income, and …

    R

  4. shibui-work-wellness-planner shibui-work-wellness-planner Public

    Shibui Planner is a full-stack productivity and wellness application designed to help users maintain balance between focused work and physical activity. Built with Flask, SQLAlchemy ORM, and a 4-ta…

    Python

  5. material_selector_shinyApp material_selector_shinyApp Public

    Interactive Shiny app for exploring and comparing construction materials. Includes dynamic filtering, Ashby-style plots, and radar chart comparisons, with a polished themed UI.

    R

  6. metro-status-prediction-pipeline metro-status-prediction-pipeline Public

    Predicting U.S. metro status using structural cost-of-living shares and machine learning.

    Python