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Kaleb Thompson

Kaleb Thompson

Product-minded data & AI leader

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Product-minded data and AI leader with 11+ years building and running the data and AI function at enterprise scale in regulated industries. Five promotions in eleven years at a Fortune 1000 natural-gas utility — analyst to head of the data organization — where I built and led a team of 12–14, owned a $3M+ budget, and architected a 40-person, three-pod data and AI organization spanning data science, data engineering, and data product management. I set the strategy and still ship the platforms myself.

Experience

  1. Principal Architect & Head of Data Engineering · Confidential

    2026 – Present

    Leading platform architecture and the data-engineering function. (Employer confidential for now.)

    Architecture Data Engineering Leadership
  2. Principal AI Architect · ONE Gas

    2025 – 2026

    Tulsa, OK

    Sole AI and data architect for the enterprise, reporting to the Chief Data & AI Officer. Architecture lead across data and AI for five business units, 20+ AI initiatives, and a $1–2M annual portfolio.

    • Architected a 40-person, three-pod data & AI organization — data science, data engineering, and data product management — that consolidated under the Chief Data & AI Officer.
    • Built an autonomous LLM agent (Claude / GPT-4) that refactors SQL Server stored procedures, views, and T-SQL into Snowflake SQL + dbt models — 100+ objects at 85%+ accuracy, cutting per-object migration from weeks to hours.
    • Shipped production GenAI: a Safety Copilot scaled from 300 to 2,000+ field users and a legislative risk-analysis tool that cut analysis time 70%, plus enterprise RAG over SharePoint and SQL sources.
    • Built a real-time mixed-integer-programming dispatch optimizer for 200+ field technicians, improving emergency SLA from ~50% to 67%+.
    • Replaced a $250K/yr Gartner advisory product with a custom internal AI intake & innovation platform (React, Tailwind, Valkey, Argo CI/CD, GHCR).
    • Led a $200K cloud-AI vendor evaluation (Azure AI Foundry vs. AWS Bedrock) and set enterprise reference architectures for LLM orchestration, agents, and RAG.
    Applied AI LLMs / RAG MLOps Architecture
  3. Head of Enterprise Data & Analytics (Senior Manager) · ONE Gas

    2022 – 2025

    Tulsa, OK

    Owned the company's data strategy, engineering, and science programs across all business lines. Grew the team to 12–14 and managed a $3M+ budget.

    • Built the Snowflake + dbt platform from scratch with CI/CD, Git workflows, and DataOps adopted as the enterprise baseline — 90% improvement in analytical workload execution vs. on-prem SQL Server.
    • Replaced batch ETL with sub-second CDC streaming from Oracle and SQL Server into Snowflake via Qlik Replicate, saving ~$300K/yr.
    • Delivered 30+ enterprise data products and stood up a Power BI Center of Excellence that cut time-to-insight 60%.
    • Reclassified Snowflake spend as Direct Materials to enable CapEx treatment of development costs (OpEx → CapEx).
    Data Platform Snowflake / dbt Leadership Governance
  4. Manager, Data Science & Analytics · ONE Gas

    2019 – 2022

    Tulsa, OK

    Led the data-science function and its production ML portfolio; built and led a cross-functional team of engineers and scientists.

    • Built RADAR, a pipeline-strike prediction model (Python, scikit-learn, MLflow, 811 tickets + GIS) that outperformed a $1M/yr vendor at under $100K — leading to a new Damage Prevention department.
    • Deployed Azure Databricks as the company's first cloud ML environment.
    • Shipped Payment Pathways, an ML model scoring bill-pay risk to improve collections recovery.
    Machine Learning MLOps Optimization
  5. Lead Data Scientist / Data Engineer · ONE Gas

    2015 – 2019

    Tulsa, OK

    Founded the organization's data-science practice and built its first cloud ML capability.

    • Shipped a meter-read exception classifier that reduced manual review 60% (~$40K/yr), rolled out humans-in-the-loop to earn operator trust.
    • Built predictive capital-project estimators that reduced budgeting variance 10–20%.
    • Delivered field-technician route optimization saving 500+ hours/yr.
    Machine Learning Python Azure Databricks
  6. Data Analyst · NRG Energy (Direct Energy)

    2014 – 2015

    Tulsa, OK

    Reconciled billing and revenue data across 20+ utility partners.

    • Recovered $1M+ in missed revenue across 20+ utility partner datasets via SQL reconciliation.
    • Led the transition of transaction-management operations from Toronto to Tulsa.
    SQL Analytics

Skills

AI & GenAI

  • LLMs in production (Claude, GPT-4)
  • RAG & agents
  • Prompt engineering
  • Hugging Face
  • AI governance

ML & MLOps

  • scikit-learn, XGBoost
  • MLflow, Databricks ML
  • Model registry & monitoring
  • Mixed-integer programming (PuLP)

Data Platforms & Cloud

  • Snowflake
  • dbt
  • Databricks
  • Azure (AI Foundry, ADF, DevOps)
  • AWS (Bedrock)
  • Qlik Replicate (CDC)

Languages

  • Python
  • SQL
  • R
  • PowerShell
  • Bash

Architecture & Modeling

  • Medallion architecture
  • Kimball star schemas
  • RBAC
  • Data governance
  • Semantic layer

Leadership

  • Team building & org design
  • Budget ownership ($3M+)
  • Vendor evaluation & RFPs
  • Executive stakeholders

Education

M.S. Business Analytics & Data Science

Oklahoma State University · Graduate Certificate in Data Mining

B.S. Business Administration (Finance)

Oklahoma State University

Speaking & Leadership

Speaker & Panelist

Utility Analytics Institute (UAI)

Spoke at UA Week in San Diego, and served on UAI panels.

2022

Community Lead — Natural Gas Analytics Community

Utility Analytics Institute (UAI)

2019 – 2022

Corporate Advisory Board Member

M.S. Business Analytics & Data Science, Oklahoma State University

2020 – 2026

Toastmasters

Tulsa City-County Library chapter

2019

Languages

English

Native

Brazilian Portuguese

Native / professional