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Western Governors University — M.S. Data Analytics, Data Science

Jesse Coggins

Data Analyst · Data Scientist

Nearly a decade of multi-site operations leadership translating KPI, revenue, labor, and throughput data into reporting, decisions, and process improvement — now applied across a public portfolio of analytics, machine learning, forecasting, deep learning, databases, optimization, and MLOps work.

The work worth opening first.

These cover the core story of the portfolio: end-to-end ML engineering, supervised classification on a real-world business problem, a published BI dashboard, and a hybrid analytics project that crosses supervised, unsupervised, and dimensionality reduction methods.

Additional work across market analysis, forecasting, databases, NLP, vision, optimization, and statistics.

The broader portfolio shows range: independent regional market analysis, time series, relational and NoSQL database design, text modeling, computer vision, operations research, and applied statistical work on real datasets.

Market Analysis 05

Southeast Housing Market Analysis

Regional housing-market screening framework comparing 105 Southeast metros on affordability, growth, and labor-market depth. Produces overall and balance rankings that separate low-cost markets from markets with stronger fundamentals.

Top Metro
Huntsville
Coverage
105 metros
States
11
Time Series 06

Revenue Forecasting with ARIMA

ARIMA forecasting on 731 daily revenue observations with ADF stationarity testing, differencing, parameter selection, and holdout evaluation.

RMSE
0.4887
MAE
0.3766
Obs
731
Repository →
Databases 07

EcoMart Relational + NoSQL Design

Normalized 3NF PostgreSQL design across five tables and 100,000 records with ETL staging, indexes, CTEs, and reusable analytical views — plus a parallel MongoDB implementation with aggregation pipelines and compound indexes.

Tables
5
Records
100K
Schema
3NF
Repository →
NLP 08

Sentiment Analysis with BiLSTM

Bidirectional LSTM sentiment classifier with sequence preprocessing, tokenization, padding, and evaluation on a labeled test set.

Accuracy
76%
F1
0.72
Repository →
Computer Vision 09

Seedling Image Classifier

Convolutional Neural Network for multi-class classification of plant seedling species, with trained model artifact included for inference and inspection.

Accuracy
66.62%
Classes
12
Repository →
Statistics 10

Statistical Analysis + Market Basket

Five notebooks covering linear regression, logistic regression, PCA, hypothesis testing (ANOVA, Mann-Whitney U, Chi-Square) on health insurance data, and Apriori market basket analysis on 8,234 retail transactions surfacing high-lift association rules.

Top Lift
88.2
Transactions
8,234
Repository →
Optimization 11

Cargo Network Optimization

Linear programming formulation of a multi-node cargo transshipment network in PuLP, with capacity constraints and explicit verification of feasible flows.

Optimal Cost
$200,863.75
Status
Optimal
Repository →

The tools behind the work — organized the way I actually use them.

Not an exposure list. Every tool below shows up in one or more of the ten public portfolio repositories, used on real data to produce real outputs.

a.

Languages

  • Python
  • SQL
b.

Analytics & BI

  • Tableau
  • pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • KPI Reporting
  • Dashboard Development
  • EDA
c.

Statistical & Machine Learning

  • scikit-learn
  • statsmodels
  • Random Forest
  • Logistic Regression
  • K-Means
  • PCA
  • ARIMA
  • Hypothesis Testing
  • Classification
  • Clustering
  • Forecasting
  • Association Rule Mining
d.

Deep Learning & NLP

  • TensorFlow
  • Keras
  • CNN
  • Bi-LSTM
  • Computer Vision
  • Sentiment Analysis
  • Model Evaluation
e.

Data Engineering & Deployment

  • PostgreSQL
  • MongoDB
  • ETL
  • Docker
  • FastAPI
  • MLflow
  • DVC
  • GitLab CI/CD
  • pytest
f.

Operations Research

  • PuLP
  • Linear Programming
  • MILP
  • Transshipment Modeling

Operations leadership is where the business framing comes from.

Nearly a decade managing multi-site operations, KPI tracking, labor, throughput, and performance reporting. The portfolio work is built to support decisions — not just produce models — because that is what the day job has always required.

  1. Jan 2022 — Feb 2026

    General Manager

    Xtreme Car Wash · Anniston, AL

    • Tracked and analyzed daily KPIs — revenue, labor cost %, and customer throughput — across three sites, using real-time performance data to drive staffing decisions and reduce operational inefficiencies.
    • Designed and delivered structured weekly and monthly business intelligence reports for ownership, translating raw site-level data into financial and operational insights that informed executive decisions.
    • Applied performance trend analysis to manage and coach 20+ employees across multiple locations, identifying execution gaps and improving accountability through data-driven feedback.
  2. Mar 2020 — Jan 2022

    Site Manager

    Xtreme Car Wash · Anniston, AL

    • Monitored wash volume, labor utilization, and throughput metrics daily; used demand pattern analysis to optimize scheduling and maintain operational targets.
  3. Oct 2017 — Mar 2020

    Site Manager

    International Car Wash Group · Gadsden, AL

    • Managed daily operations and staff performance at a high-volume site, sustaining service quality and operational KPIs through consistent process execution.

Where the analytical foundation was built.

  1. Mar 2026

    M.S. Data Analytics — Data Science

    Western Governors University

    Coursework: Machine Learning, Statistical Analysis, Data Mining, MLOps, Deep Learning, Optimization, Database Management.

  2. May 2024

    B.S. Management

    Jacksonville State University

    Summa Cum Laude · Special Honors in Management.

  3. Aug 2022

    A.S. General Studies — Business Administration

    Gadsden State Community College

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Jesse Coggins Resume

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