I am an AI and Data Strategy Leader committed to advancing transformative solutions in the public sector. My work focuses on harnessing technology to improve government efficiency, transparency, and service delivery.
Previously, I served as Oklahoma’s State Data Strategy Manager, leading initiatives that leveraged artificial intelligence, governance frameworks, and scalable data systems across 180+ agencies. My expertise spans generative AI, natural language models, and advanced analytics—tools I have applied to help state government become more efficient and data-driven.
Throughout my career, I have built and deployed AI systems that create real-world impact, from statewide generative AI deployments to solutions for geospatial data extraction and economic analysis. I specialize in designing workflows and data pipelines that reduce costs, scale effectively, and improve decision-making.
With a Master’s in Political Science and a background in policy analysis, I bring a perspective that bridges technical skill and public policy insight. My career goal is to continue pushing the boundaries of AI in government—helping to build systems that are more efficient, more transparent, and more responsive to the people they serve.
Impact Highlights
These projects illustrate my approach to building responsible, scalable AI systems that advance efficiency, equity, and public participation.
Scaling generative AI across 180+ state agencies.
As State Data Strategy Manager, I led the introduction of artificial intelligence into government operations, including deploying ChatGPT Enterprise across 180+ state agencies. I established governance frameworks, built scalable data pipelines, and created adoption pathways for generative AI to enhance efficiency and transparency in statewide service delivery.
I also contributed to the Governor’s Task Force on Emerging Technologies and authored statewide AI governance policy focused on safeguarding citizen data.
Open-source AI tools lowering barriers to campaign strategy.
I founded Nudge Politics, an early-stage open-source initiative building AI and data tools to help campaigns adopt modern, data-driven strategy. The platform integrates advanced analytics with narrative insights to support down-ballot candidates in running more efficient and effective campaigns.
By lowering technical and financial barriers, I aim to make sophisticated tools accessible to organizations that have historically lacked them, while emphasizing transparency and adaptability so campaigns of all sizes can strengthen voter engagement and make smarter strategic decisions.
Driving enterprise-wide efficiency through AI adoption.
As Senior Data Scientist at Paycom, I lead AI strategy and internal consulting initiatives that drive automation and efficiency across the company. I design and deploy production-ready NLP and LLM solutions, from document-processing pipelines to conversational interfaces, helping business units reduce costs and streamline workflows.
I also guide a growing data science team, aligning projects with organizational priorities and ensuring scalable, responsible AI adoption.
Work Experience
From Civic Engagement to AI Strategy
Building an open-source civic-tech initiative to equip campaigns with AI and data tools.
Designing platform modules that integrate analytics with narrative insights to lower barriers to modern campaign strategy.
Leading early development, open-source contributions, and partnerships to scale access to responsible political technology.
Developed a data and AI strategic plan for a core business unit, aligning technical initiatives with enterprise priorities and creating a roadmap for responsible AI adoption.
Transformed financial operations by deploying an AI-powered PDF processing pipeline (Qwen2.5-VL) that accelerated financial close by 75% and enabled near real-time submissions.
Strengthened financial governance by designing a containerized ETL pipeline with Splunk monitoring, eliminating reporting discrepancies and reducing operational risk.
Advised leadership on AI investment and provided mentorship to a growing data science team, ensuring projects delivered both technical excellence and business value.
Spearheaded Oklahoma’s adoption of ChatGPT Enterprise across 180+ agencies.
Built statewide governance frameworks, scalable data pipelines, and a Master Person Index for 4M residents.
Directed econometric and geospatial AI analyses to inform fiscal policy and improve statewide service delivery.
Advised the Governor’s Task Force on Emerging Technologies and authored statewide AI governance policy.
Launched the public sector’s first generative AI chatbot, automating citizen inquiries and improving responsiveness by 25%.
Developed anomaly detection and classification models, identifying $15M+ in potential procurement savings.
Built an NLP-based RAG search engine that cut policy document retrieval time in half.
Created performance-informed budgeting models to align funding with measurable outcomes.
Analyzed 10 years of survey panel data on governance and climate change using regression and latent profile analysis.
Led statistical analysis of 13 waves of COVID-19 surveys to inform health policy and communication.
Designed a PhD-level data visualization course for social scientists.
Developed a community sustainability model using UN indicators to evaluate rural resilience.
Conducted data analysis across all 77 Oklahoma counties to provide tailored policy recommendations.
Supported grassroots voter outreach through canvassing, phone banking, and event coordination.
Engaged with local stakeholders and campaign staff to expand community participation and mobilization.
Contributed to campaign data entry and voter contact tracking using NGP VAN and MiniVAN.
Led the design and deployment of generative AI and machine learning systems that improved efficiency, strengthened decision-making, and unlocked new capabilities across government and enterprise operations.
Developed governance frameworks and organizational AI strategies to ensure responsible adoption, data security, and ethical use. Built cross-agency standards that balanced innovation with compliance and public trust.
Built scalable data infrastructures and analytics platforms that deliver actionable insights, support fiscal and policy planning, and drive measurable improvements in organizational performance.
Directed and mentored interdisciplinary teams, aligning technical expertise with strategic objectives to successfully execute high-impact AI and data projects at scale.
Education
My academic training bridges political science, public policy, and advanced data science methods, providing the foundation for my AI and governance work.
Concentration in Public Policy
Research Focus: Public Trust, Technology Policy, Causal Inference, Natural Language Processing, Survey Methodology
Developed the Actor Evaluation and Trust Framework (AETF), a theoretical model employing structural equation modeling to analyze trust-formation processes during public health and natural disaster crises.
Concentration in Public Policy
Research Focus: Public Trust, Environmental Policy, Survey Methodology
I am actively pursuing research at the intersection of AI, governance, and public policy, with a focus on how technology shapes narratives, trust, and decision-making.
AI Narratives in Public Policy – Examining the Role of Generative Models in Policy Framing
Investigates how generative AI systems construct narratives around policy issues, applying a popular policy process theory to evaluate implications for public discourse, agenda-setting, and democratic debate.
The Actor Evaluation and Trust Framework – Redefining Public Trust and Risk Management for Crises
Introduces a theoretical framework for understanding how citizens evaluate institutions during crises, leveraging survey data and structural equation modeling to guide governance, communication, and risk management strategies.
Thesis Paper: The Decision to Trust: An Application of Structural Equation Modeling to the Actor Evaluation and Trust Framework