Fractional · Advisory · Project · Staff aug
Work with me.
I work as senior data and AI help for teams that need it. I dig into what's actually going wrong, build the fix alongside your people, and leave it in their hands. Sometimes that's setting the direction; a lot of the time it's writing the code.
What I help with
I'll set direction
and build it.
Some teams need someone to call the shots for a while. Others just need the work done well. Usually it's both, and I'm fine either way.
Lead & strategize
Fractional data & AI leadership
I run as your head of data or AI a few days a week, making the calls, hiring, and clearing roadblocks until you're ready to bring it in-house.
Strategy & architecture
We work out what to build first, what can wait, and what to quietly drop. That covers the data underneath and the AI sitting on top of it.
AI adoption & agentic workflows
I get real AI and agent workflows running, then do the harder part: helping your team trust them enough to actually lean on them.
Design & build
Analytics engineering
dbt models, a clean shared data layer, and tests, so a number means the same thing no matter who pulls it.
Data engineering
Pipelines and back-end systems that keep working when your data suddenly gets a lot bigger.
Data science & ML
Models that make it to production and stay useful, instead of dying in a notebook nobody opens.
BI & dashboards
Dashboards people actually open, built into the tools they already use.
Engagement models
However it
fits your team.
Same me, just set up differently. We'll land on whichever one fits the problem and your budget.
Fractional
A couple of days a week, ongoing. You get a head of data or AI without paying for a full-time one.
Project
One well-defined job with an end date: a pipeline, a model, a migration, an AI workflow.
Advisory
Strategy sessions, architecture reviews, or a second opinion before you commit to something expensive.
Staff augmentation
Borrow me for a few months when you're short a senior hand and want the bar raised while I'm around.
How an engagement runs
Get it running.
Keep it fed.
Careful, no surprises, and built to keep working after I'm gone. Roughly the same whether it's a pipeline or an AI agent.
Map the terrain
First I learn where your data lives, who owns it, and what's broken. We agree on what “good” looks like before I touch anything.
Get it running
Then I build in small pieces you can watch come together, so nothing vanishes into a six-month black box.
Keep it fed, then let go
Last, we sort out who keeps it running, write down how it works, and hand it over so your team owns it instead of me.
Background
Eight years,
mostly fixing trust.
Most of my career has been making other people's data into something they could finally rely on, and growing the people around it.
- 2025 — NOW · DALLAS, TX
Independent & building
DataViking — studio + fractional workBuilding data & AI products, and stepping into teams as senior data help when they need a hand on their own.
- 2021 — 2025 · PELOTON
Sr. Manager, Data Analytics & Development
Team of 6 · backbone for a 30-person departmentWorked with VP+ leaders on growth and revenue, and looked after the hiring, promotions, and careers of the people on my team.
- 2017 — 2021 · BRINKS HOME
Lead Data Analyst / Data Scientist
The COO's right handSat between operations and revenue, led the data warehousing work, and coached around ten analysts into stronger roles.
I've been a data engineer, data scientist, analytics engineer, and analyst, and spent years leading people doing all four. That range is the point: I can see the whole picture and still get my hands dirty in any part of it.
- Snowflake
- dbt
- Airflow
- Python
- Go
- TypeScript
- Postgres
- AWS
- Claude/LLMs
- PyTorch
Case study · Gastown
Teaching a startup to take its hands off the wheel.
A three-person startup in Austin wanted to build with AI agents. Getting their setup running was the quick part. The real work was helping them plan around it, pick the right tools, and get comfortable letting the agents do the work.
They went from second-guessing every step to shipping faster than when we started.
By the end they trusted the setup enough to keep building on it without me.