Strong Business Partnership
I make it a priority to deeply understand the business context. My strong suit is partnering directly with stakeholders to build systems they trust.
Data Scientist & Analytics Engineer
Helping translate industrial complexity into pricing intelligence, structured decisions, and practical AI workflows.
Across seven years at HOLT CAT, I have grown from business-facing analysis into data science, analytics engineering, and enterprise data platform work. That progression shaped how I build: start with the stakeholder problem, learn the operating model, then design the data system behind the decision.
What I bring to the table
Operational context, technical depth, and a record of turning analysis into systems.
Analytics engineering depth
I can model the warehouse, write the SQL, shape the semantic layer, and explain the metric to operators.
Applied AI without the theater
I use AI to accelerate refactors, pipeline delivery, anomaly review, and repetitive financial workflows.
0progressive data platform experience
0delivering from raw database model to dashboard
0partnering with teams to solve business needs
0Fabric Analytics Engineer Associate (DP-600)
The work
Selected Projects & Case Studies
An interactive catalog of my analytics engineering, data science, and web development work. Toggle below to filter between enterprise accomplishments and personal applications.
01
Data Scientist, HOLT CAT
workMachine Quoting & Market-Based Pricing Engine
Architected and deployed an end-to-end pricing intelligence system powered by machine learning to automate the company's equipment quoting process.
Architecture
- XGBoost classification and regression models trained on historical deal parameters
- Snowflake Notebooks for exploratory data analysis, feature engineering, and model validation
- Streamlit interface deployed internally for pricing analysts and commercial teams
- Automated scoring pipelines running natively inside Snowflake compute layers
Impact
- Replaced manual quoting spreadsheets with dynamic machine quoting recommendations.
- Optimized transaction capture and realized margin accuracy across high-volume quotes.
- Reduced average turnaround time for pricing review from hours to near-instantaneous.
02
Analytics Engineering Lead, HOLT CAT
workEnterprise Lakehouse Migration & Platform Modernization
Co-led Project Galaxy, a massive migration from legacy Snowflake, dbt, and Tableau footprints into a unified Microsoft Fabric Lakehouse environment.
Architecture
- Medallion data lakehouse architecture (Bronze, Silver, Gold layers)
- Microsoft Fabric semantic models and automated delta parquet pipelines
- dbt data transform normalization layers translated into Fabric environments
- Enterprise-wide Power BI reports and executive analytical dashboards
Impact
- Modernized the analytics stack, reducing reliance on legacy infrastructure and third-party tools.
- Standardized metrics across multiple business divisions via Fabric Gold semantic tables.
- Established migration patterns now adopted across the entire analytics engineering team.
03
Data Architect & Integration Engineer, HOLT CAT
workCustomer Order to Invoice (COTI) Integration Pipeline
Engineered a mission-critical pipeline linking ERP and CRM data directly into monday.com to streamline the company's high-stakes Customer Order to Invoice (COTI) process.
Architecture
- Automated data extraction pipelines pulling from ERP (Salesforce, SAP/DB) and CRM systems
- Secure webhook handlers and Monday API integrations for live status synchronizations
- Cross-department notification triggers and task-reassignment workflows
- Data reconciliation models to prevent order double-entry or processing bottlenecks
Impact
- Facilitates order tracking across 10 business departments, improving delivery visibility.
- Powers the operational pipeline responsible for delivering over $1 Billion in machinery annually.
- Significantly reduced manual follow-ups and order invoice latency.
04
Lead Data Analyst, HOLT CAT
workGeospatial & Demographic Market Analysis for Facility Expansion
Conducted a comprehensive demographic and market share analysis that directly justified the capital expenditure and development of a new full-service operating facility.
Architecture
- Geospatial clustering models of customer migration patterns and fleet density
- Multi-variable regression incorporating population growth, regional GDP, and competitor share
- Interactive map visualizations and executive scenario-modeling calculators
- Financial feasibility and market share capture projections
Impact
- Directly resulted in the approval and construction of a new full-service operating facility.
- Drastically improved regional market share and reduced service technician travel times.
- Established a data-driven framework for future real estate and territory expansion planning.
05
Creator & Full-stack Developer
personalLouie Boards Charcuterie CRM & Dashboard
Built a custom, isolated CRM and order tracker for my wife's boutique charcuterie business, streamlining customer engagement and order fulfillment.
Architecture
- Next.js client interface deployed on Vercel
- Supabase PostgreSQL data layer with isolated development/production schemas
- Square API integration for transactional webhook captures and catalog syncs
- Automated SMS notifications and customer order history dashboards
Impact
- Moved customer records from manual messages into a structured CRM database.
- Automated payment-to-order workflow validation using Square webhooks.
- Saved custom product builder options directly associated with client historical preferences.
06
Creator & Backend Developer
personalNet Worth & Cashflow Management Engine
Developed a high-performance personal finance tracker to aggregate family cashflow, budgeting logs, and long-term investment progress.
Architecture
- Serverless API built using Vercel Serverless Functions and Supabase
- Cron pipeline keep-alive system to prevent database cold-start latency
- Custom transaction caching layers for speed optimization
- Interactive visualization dashboards using Recharts for surplus tracking
Impact
- Centralized transaction data and budgeting routines into a single platform.
- Established real-time cashflow projections and automated anomaly alerts.
- Optimized database performance to run queries in under 50ms using strict indexing.
Public proof
The two projects a recruiter can inspect more deeply right now.
Most of my highest-leverage enterprise work is proprietary. These public case studies show how I think when the implementation details can be shared more openly: data model, workflow design, backend decisions, and product tradeoffs.
Enterprise case studies stay on the homepage because the business outcomes are real, but the code and underlying data cannot be shared publicly.
These deeper pages are where I expose the implementation context I cannot always attach to work projects.
Creator & Full-stack Developer
Louie Boards Charcuterie CRM & Dashboard
A custom CRM, order tracker, and fulfillment workflow for a boutique food business with highly specific order details and repeat-customer preferences.
Strongest signal for recruiters: product-minded data design, API integration, and pragmatic workflow automation for a live small-business use case.
Read case studyCreator & Backend Developer
Net Worth & Cashflow Management Engine
A household finance platform focused on transaction aggregation, budgeting visibility, long-term net worth tracking, and performance-conscious query design.
Strongest signal for recruiters: end-to-end product engineering with data modeling, serverless backend behavior, performance tuning, and decision-oriented visualization.
Read case studyCapabilities
The stack I use to move from question to system.
I am strongest when the work spans business discovery, warehouse logic, semantic modeling, automation, and a clear executive-facing answer.
Data Platforms
Lakehouse, warehouse, and schema design for operational analytics.
Analytics Engineering
Reliable transformations and semantic layers for decision-ready metrics.
BI and Executive Reporting
Dashboards and models that translate operational data into clear decisions.
Machine Learning Systems
Predictive systems for industrial logistics, bottlenecks, and fleet optimization.
AI Workflow Engineering
LLM-assisted development and agentic workflows for delivery acceleration.
Product Engineering
Full-stack data products deployed on modern serverless infrastructure.
Experience
A career arc from operations to data science.
My background started with account ownership and forecasting, then moved into BI, cloud pipelines, machine learning, pricing systems, and enterprise data modernization.
Data Scientist
- Architected a market-based pricing application for commercial machinery rate analysis.
- Spearheads Project Galaxy, a migration into Microsoft Fabric Lakehouse architecture.
- Productionized ML systems for logistics bottlenecks and fleet distribution optimization.
- Introduced AI-first development workflows that improved delivery speed by more than 35%.
Data Analyst 3
- Engineered Azure and Snowflake ETL/ELT workflows and reduced ingestion latency by 25%.
- Audited warehouse cost drivers and identified redundant compute and query overhead.
- Automated operational asset-health workflows in Alteryx, reducing manual reporting by 40%.
Data Analyst 2
- Managed enterprise Power BI and Tableau reporting suites across billions of records.
- Analyzed machinery transaction and telemetry patterns for regional operating teams.
Sales Executive
- Managed regional accounts, forecasting, pipeline analysis, and logistics coordination.
- Built the business foundation that informs current analytics and product judgment.
Master of Science, Advanced Data Analytics
University of North Texas, 2018 - 2019
Bachelor of Science, Sports Management
East Texas A&M University, 2010 - 2014
Microsoft Certified: Fabric Analytics Engineer Associate
DP-600 certification
Active technical communities
dbt Global Community and Microsoft Fabric Community Conference, 2026
Recruiter flow
If this aligns with what your team is building, I'd love to connect.
I am looking for work where data science, analytics engineering, and applied AI are tied to real operating decisions. Email and LinkedIn are the fastest ways to reach me.