Kevin Joy
Data Analytics Professional
Financial Data Analyst & Deputy Branch Head at Naval Cost Agency | Operations Research & Machine Learning Expert | Data Strategy | Specializing in Predictive Modeling & Cost Estimation
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Financial Data Analyst & Deputy Branch Head at Naval Cost Agency | Operations Research & Machine Learning Expert | Data Strategy | Specializing in Predictive Modeling & Cost Estimation
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I am a passionate data analytics professional with over 15 years of experience transforming complex data into actionable insights. Rising quickly through leadership positions in government as a Financial Data Analyst and Cost Estimator, I excel at making data accessible and meaningful for decision-makers at all levels.
I'm particularly enthusiastic about leveraging open-source technologies to build cost-effective, scalable solutions that can be rapidly deployed. My technical expertise spans Python, R, SQL, machine learning, and data visualization, complemented by my work developing innovative tools that harness large language models and AI as strategic advantages for growing organizations.
I specialize in right-sizing data solutions for organizations, ensuring they maximize value without excessive infrastructure investments. My mission is to empower organizations with sustainable data capabilities that advance their goals and amplify their impact.
Developed Retrieval-Augmented Generation using HuggingFace ecosystem and LLAMA 3.3 that allows users to upload and have "conversations" with their data.
Developed a rapid-turnaround long-range forecasting tool designed to optimize future fleet architecture and acquisition planning, using AWS and Machine Learning.
Developed an advanced escalation calculator using open-source data from FRED, integrating a web application with automated data pipelines.
The Cost Estimating Reliability Dashboard analyzed over 100 Major Defense Acquisition Programs using NLP to clean messy data and automate analysis.
Developed Python-based library that provides a framework for cost estimates within the Python Ecosystem, including Monte Carlo simulation capabilities.
Analyzed several analogous programs EVM data using non-linear optimization algorithm to solve for the Weibull distribution parameters that best predicts future outlays.
Leading high-performing teams to develop cost models, analyze risk tolerance, and assess the long-term financial impact of acquisition programs.
Built financial dashboards and interactive visualizations to support real-time decision-making and applied advanced statistical models to predict program costs.
Developed cost models and analysis tools to support program evaluation and budgetary decisions.
Graduate Certificate, Data Science
Naval Postgraduate School, 2020
Masters of Science, Operations Research
Kansas State University, 2014
Bachelors of Science, Operations Management
University of Maryland, Robert H. Smith School of Business, 2010
Feel free to reach out if you're interested in collaborating or have questions about my work.
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