Curriculum Vitae
Gavin Boss
Data & Business Analytics | Python • SQL • Power BI • Predictive Analytics
Analytics professional with 8+ years of experience solving complex problems, identifying meaningful patterns, and translating analytical findings into actionable recommendations for senior decision-makers.
Professional Summary
Analytics professional with 8+ years of experience transforming complex information into actionable insights that support strategic and operational decision-making.
Completed a Master of Science in Applied Business Analytics from Boston University, combining extensive professional analytical experience with hands-on technical expertise in Python, SQL, Power BI, statistical modeling, machine learning, predictive analytics, forecasting, simulation, optimization, and data visualization.
Experienced in developing analytical assessments, identifying trends and anomalies, evaluating competing explanations, improving analytical workflows, and communicating complex findings to senior technical and non-technical stakeholders.
Core Competencies
Data Analytics & Programming:
Python • SQL • R • Pandas • NumPy • SciPy • Scikit-learn • Jupyter Notebook
Business Intelligence & Visualization:
Power BI • Tableau • Excel • Power Query • Matplotlib • KPI Reporting • Dashboard Development
Data Science & Statistics:
Predictive Modeling • Statistical Modeling • Regression • Classification • Random Forest • Decision Trees • KNN • K-Means Clustering • PCA • Forecasting • Bayesian Analysis • Monte Carlo Simulation • MCMC • Data Mining • Optimization
Professional Analytics:
Executive Reporting • Data Storytelling • Decision Support • Stakeholder Communication • Cross-Functional Collaboration • Process Improvement • Analytical Leadership • Structured Problem Solving
Professional Experience
Mid All-Source Analyst — Amentum
United States Central Command (USCENTCOM) | Tampa, FL
Mar 2025 – Present
- Analyze continuous, high-volume multi-source reporting to identify trends, relationships, anomalies, emerging indicators, and risks that inform strategic and operational decisions.
- Translate complex and ambiguous organizational questions into structured analytical problems, measurable indicators, and decision-ready assessments.
- Integrate multiple data and information sources to evaluate competing explanations, identify meaningful patterns, and produce defensible analytical findings.
- Develop recurring analytical reports and executive briefings that communicate complex findings and recommendations to senior decision-makers.
- Collaborate across organizational and functional boundaries to develop integrated assessments, resolve information gaps, and improve analytical quality.
- Apply structured analytical methods, validation processes, and quality controls to improve the accuracy, consistency, and reliability of analytical products.
- Develop and refine repeatable analytical workflows and documentation to improve efficiency, standardization, and knowledge transfer.
Education
Boston University
Master of Science in Applied Business Analytics
Jan 2025 – Aug 2026
Completed June 2026 | Degree Conferral August 2026
Graduate study focused on:
- Machine Learning & Predictive Analytics
- Statistical Modeling
- Business Intelligence
- Data Mining
- Forecasting & Time Series Analysis
- Monte Carlo Simulation
- Bayesian Analysis
- Optimization & Decision Modeling
- Data Visualization
- Business Strategy & Analytics
University of Maryland Global Campus
Bachelor of Science in Cybersecurity Management and Policy — Honors
2021 – Dec 2024
Selected Analytics Projects
Predictive Salary Modeling
Developed and compared generalized linear regression, polynomial regression, and Random Forest models in Python to predict salary outcomes and evaluate influential features.
Methods: Regression • Random Forest • Feature Analysis • Model Evaluation
Tools: Python • Pandas • NumPy • Scikit-learn • Matplotlib
Market Segmentation & Machine Learning
Applied classification, clustering, NLP, and dimensionality reduction techniques to business and market datasets to identify patterns and meaningful segments.
Methods: KNN • Decision Trees • Random Forest • K-Means • PCA • TF-IDF
Tools: Python • Pandas • Scikit-learn
Forecasting, Simulation & Optimization
Developed quantitative decision models to evaluate alternative strategies under uncertainty, including:
- 50,000-path demand simulations
- 100,000-trial optimization analyses
- Time-series forecasting
- Bayesian probability modeling
- Risk-constrained resource allocation
- Net Present Value decision frameworks
Methods: Monte Carlo Simulation • Bayesian Analysis • Forecasting • Optimization • Sensitivity Analysis
Tools: Python • NumPy • SciPy • Pandas
Technical Skills
| Area | Technologies & Methods |
|---|---|
| Programming | Python, SQL, R |
| Python Analytics | Pandas, NumPy, SciPy, Scikit-learn |
| Business Intelligence | Power BI, Tableau, Excel, Power Query |
| Visualization | Matplotlib, Power BI, Tableau |
| Machine Learning | Regression, Random Forest, Decision Trees, KNN, K-Means |
| Statistics | Hypothesis Testing, Bayesian Analysis, MCMC, Statistical Modeling |
| Decision Science | Forecasting, Monte Carlo Simulation, Optimization, Risk Analysis |
| Development | Git, GitHub, Jupyter Notebook |
Professional Strengths
- Analytical Problem Solving
- Executive-Level Communication
- Data Storytelling
- Cross-Functional Collaboration
- Stakeholder Management
- Process Improvement
- Analytical Leadership
- Decision Support
- Technical Documentation
Connect
LinkedIn: linkedin.com/in/gavinboss
GitHub: github.com/gavinboss
Project Portfolio: gavinboss.github.io/projects.html ```