Moving organizations from counting to deciding.

I am an Analytics Director with 15 years leading data teams across tech, fintech, and gaming, specializing in behavioral data, decision frameworks, and AI-assisted workflows. This page covers that work, along with newer projects focused on bringing that same expertise and approach to mission-driven, progressive spaces like local journalism and civic tech.

15+
years behavioral data and strategy
3
teams built and scaled across multiple sectors
2
0-to-1 data stacks and intake frameworks
Decision Frameworks AI-Assisted Workflows Team Leadership Data Culture Change
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Right math + wrong question = wrong result.

Ask for average spend on the site, and you've already decided that's the right lens on the real question. We've moved from "I don't need data to decide" to "I must have data to decide" - but that's not the same as being data-informed. Data-informed means the analyst is in the room from the start, making sure the question is right, not just the math.

That's the work I actually do — push back on the metric-first ask, get to the decision underneath it, and build the analysis around what will actually change someone's mind.

I'm always thinking about how data and AI can solve problems that show up across very different industries, not just the ones I've worked in. These projects are where that thinking gets tested: some grown out of gaming and fintech work, others newer explorations into spaces like local journalism and campaign strategy.

Analytics Intake Tool

An AI-powered tool moving analytics teams from reactive mode into prioritized sprints by handling repetitive intake tasks automatically.

AI + Analytics Python LLM Architecture
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Message Design and Experimentation

A Streamlit prototype exploring how local-news messaging research could become an interactive coach for newsrooms, built with a journalism funder's grantee network in mind.

Python Streamlit Local News
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Conversation Mapper

A semantic clustering prototype for campaigns and advocacy orgs, exploring how to engage audiences by how they actually want to be reached: replying, reposting, or sharing, not just broadcast at.

Semantic Clustering Campaigns & Advocacy
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Why the industry doesn't matter.

On the surface, gaming and fintech couldn't be more different. But at their core, the data problems are identical: stakeholder requests rarely match the actual question that needs answering. Figuring out what data is really needed - and why - is the job, no matter the industry. That's why the same analytical instincts deliver results, even when the domain completely changes.

What changes
  • Vocabulary and metrics
  • Volume and speed
  • User segments
What transfers
  • Building trust in the data
  • Avoiding the monolithic customer trap
  • Turning vague requests into decision-driving results
Jen Airoldi

I've spent fifteen years or so trying to figure out what questions are worth asking of data - not just pulling the answers, but knowing which problem is actually worth solving. That skill has carried across two industries with almost nothing else in common: games and fintech. What transferred wasn't domain knowledge, it was asking questions in a goal-focused way, working back from what actually matters.

Data is most powerful when it's asking the right question — not when it's confirming the answer someone already had.

Analytics team leadership & build-out SQL & modern data stack (BigQuery, Snowflake, dbt) A/B testing & experimentation design Behavioral & lifetime-value segmentation LLM integration & agentic AI tooling Executive & cross-functional stakeholder management Analytics maturity & data culture change Mentorship & team scaling

It wasn't a straight line.

Seven stops, a winding path, and the lesson each one left behind.

Water Management District → M.S. Math
The Beginning: Following the Data

I initially planned on working in environmental policy, with my first job at a Water Management District in Florida. Entry-level jobs there happened to be managing water quality data. Being out on the water scooping up samples was fun, but being at my desk building a Microsoft Access database was even more fun. I decided to go back for a more quantitatively oriented master's degree, and stepped from there into the world of tech.

Data Infrastructure Systems Thinking
Lesson carried forward
What you end up loving to do might not be what you had imagined it would be.
IT Consulting · 1997–2011
The Long Runway: IT Consulting

In my long stint in IT Consulting, I became the person who made sure the application we were building was really answering the business needs. This meant becoming great at learning new domains quickly, and at the time also meant jumping in on all the data work. It was the unglamorous, carrying-water part of the project, but it fit my goal-oriented personality well to keep things moving forward. Over time, I realized I loved solving problems with data more than coding widgets.

Stakeholder Alignment Requirements Translation
Lesson carried forward
Understanding how people will use your product is essential to making something lasting.
Zynga · 2011–2013
Finding My People: Games and Analytics

I met someone at a party who ran a game company and thought it sounded like the most fun group of nerds I could work with. I was right, and I was so lucky to be able to learn data analytics with a groundbreaking group of fantastic people at Zynga, my first games job. I launched a half-dozen games, absorbed an amazing amount of analytics, and learned that disciplined focus is what protects a team's energy and ensures analytics efforts directly move the core mission forward.

Prioritization Player Analytics
Lesson carried forward
Saying no the right way means making sure you're focusing on the questions that truly move the business forward.
Big Huge Games · 2013–2019
Building From Scratch: Games Strategy

At Big Huge Games, I was the first data person and the first product manager, both producing the analysis and consuming it. We built DomiNations, a $175M mobile strategy game still running today. It was a lot of learning on my feet to do both roles at once, and I'm immensely grateful to my first direct reports for helping to really forge the way.

0→1 Build Team Development
Lesson carried forward
I love developing great folks and watching them grow.
Facet Wealth · 2019–2022
The Mission Problem: Fintech

I joined Facet to work somewhere with a mission, democratizing financial planning for people outside the traditional income brackets. I was the first data hire, taking us from Excel and chewing gum to a production staff and fantastic team. The highest-value work wasn't just technical, it was building an organizational culture where data guides strategy rather than rubber-stamping pre-existing assumptions.

Trust & Change Management Fintech
Lesson carried forward
Building trust in data is as important as building the data itself — small cracks in confidence become craters.
Electronic Arts / Tiburon · 2022–2026
The Biggest Build: Transforming a Studio

I walked into a team that had been leaderless for six months, two of five analysts gone before my first major launch, and we delivered more with a skeleton crew than the full team had the year before. I transitioned the team from reactive order takers to strategic thought partners by establishing a structured intake framework focused on decision intent, and over my four years shifted the ethos from reactive to proactive — so that we were able to do deep dives that drove actual change and didn't just confirm hypotheses.

Team Leadership Process Design
Lesson carried forward
Rebuilding a team from the ground up teaches you more about leadership than inheriting a strong one ever could.
Sabbatical · 2026
Now: The Intentional Pause

I left EA earlier this year to think carefully about what comes next, and to make a deliberate move into a mission-oriented space. I've started to build some tools to continue to test ideas and explore questions in domains I'm less familiar with.

Product Exploration AI Tooling
Lesson carried forward
There are three things that get me excited about a job — the people, the data, and the mission — and I want the next step in my career journey to have all three.
01
Novel problems, where the contribution is the reframing
02
Intellectual co-creation with people willing to push back
03
A visible line from a finding to a decision
04
Permission to say the plain, unpopular thing
05
Building something new, before the shape is settled

Let's build something that matters.

If you're working on a problem where the right question matters as much as the right math, I'd like to hear about it. Email is the fastest way to reach me — LinkedIn and my resume are below too.