Report on what actually works when people shop online, using checkout data nobody else has.

Product.ai is the verified truth layer for shopping: when a person or an AI agent needs to know what is actually true about a purchase, we answer with proof. SimplyCodes is the first proof at scale, the code verification service whose robots run real checkouts and test discount codes so shoppers only see codes that work. It earns about $22 million a year. Profitable. Bootstrapped. Founder-owned since 2009. No outside investors. No board. Fewer than twenty operators, outbuilding companies 10x our size.

Why This Role Exists

We sit on one of the largest first-party records of online savings anywhere: years of robot-run checkouts, code tests, and shopper behavior across hundreds of thousands of stores. When we turn a slice of that record into a study, it gets cited.

Our studies earned hundreds of pickups and brand mentions across our two brands this year, and that coverage is where our citations in AI answers come from. The distribution behind it is widening: proactive story pitches, plus a standing reactive lane where reporters come to us for savings data. It now needs studies faster than we can publish them. This seat exists to be that supply. Every citation makes Product.ai a source those engines trust about a purchase, and that, not traffic, is how we intend to win. It is the first seat on this desk. The studies are yours, and you help shape the standards and the beat.

The System You'll Need to Model

  • Data-driven public relations as a supply chain. Proprietary first-party data becomes a citable study; the study rides two distribution lanes, proactive pitches and reactive reporter queries, into press coverage and AI answers. Every serious research-communications shop runs this loop. Ours runs on data nobody else has, and the study is the unit of leverage.
  • A real warehouse with real traps, and a moat that was measured rather than scraped. The estate is BigQuery-resident: Search Console, GA4 behavioral events, affiliate commissions, code-test outcomes. Large estates lie to the careless through settlement lags, event-taxonomy breaks, and dishonest denominators, so the craft is finding the trap before the number goes to print. What you print stands on checkouts we measured ourselves, ground truth rivals cannot buy.
  • Two citation markets with different physics. Journalists are pitch-driven and relationship-gated; AI answer engines are retrieval-driven and quotability-gated. Being named and being cited are separate outcomes in both, and a study that wins one can lose the other.
  • Agents as research staff, and verification as the craft that makes them usable. Warehouse pulls, research sweeps, and first drafts run through agents here; the job is proving what they hand back. What a golden check looks like for a research claim, which tests catch a silent join fanout or a survivorship artifact, when you re-pull a number by hand. Generation is the cheap part. The verdict is yours, and an unverified agent number in print is the one unrecoverable mistake in this seat.
  • Cortex, the newsroom you publish inside: the shared AI brain that runs the company and the product family we sell, it answers its own questions from more than 8,600 documents. A newsroom data desk like this ran three people in 2023; the agent tooling is why it is one seat here. The company moves weekly, nobody hands you a brief, and reading where the system is going is part of the job.

If reading that energizes you, keep going. If it feels overwhelming or underspecified, this isn't the right fit.

What You Will Own

  • Studies, end to end. From warehouse query to published study to story brief: four to six first-party data studies a month across SimplyCodes and Product.ai. Some are flagship studies; the rest are fast-turn data answers for reporters and answer engines covering working rates, code-test outcomes, shopper behavior, and survey panels. You bring SQL fluency on messy data, statistical honesty about denominators and time windows, and ledes an editor would keep; here you grow into agents as research staff, adversarial verification, and AI-engine quotability.
  • Primary reporting. Expert interviews, shopper panels, and merchant conversations, with one live reporting thread open at all times, because "we spoke with 10 AI-shopping experts" is a story class no rival can scrape. The checkout record stays the ground-truth spine; interviews supply the human context.
  • The canonical stat surfaces. The numbers the press and answer engines quote, kept fresh, sourced, and honest. When a study calls for social copy, you supply the data moment; our brand and content team owns that channel.
  • The seat, chartered. You work directly with Dakota Nunley, our Head of Search Product, who runs the research program and its beat. Within your first quarter you co-sign a seat charter anchored to one number: published studies that clear a stated method bar at this cadence, plus a clear split between what you publish directly and what your lead reads first.

Who You Are

You reason about numbers the way a good editor reasons about sources: what would make this wrong, what is the honest denominator, and what time window the claim covers. You feel the difference between a finding and a query artifact, update fast when your model is wrong, and write clearly because the written study is the meeting.

You go to the data first. Agents run warehouse queries, research sweeps, and verification passes under your direction, and because you can do every step yourself — the pull, the sanity checks, the draft, the pitch note — you know when to trust or reject what an agent hands back.

You have published data stories that stand on numbers you pulled yourself, whether on a newsroom data desk, in a data journalism program, on a research team, or on a beat you ran with a scraper and a spreadsheet. We judge the artifact and the reasoning wherever you did the work, with no degree required.

Who this isn't for. Wrong if you need data handed to you in a brief; here the story starts in the warehouse with you holding the query. Wrong if you analyze without publishing, or publish takes instead of datasets. Wrong if personal brand or a masthead logo matters more than the dataset under the byline, or if AI-native means a chat window instead of directing agents and owning verification verdicts. You will be happiest here if a good month is a flagship study and fast-turn answers shipped, cited by a reporter or answer engine, with one interview thread open.

How We Hire

We evaluate demonstrated performance on work-relevant tasks in four steps:

  1. Async video screen. Brief and on your own time, about fifteen minutes. We want to see how you think, not how you present.
  2. Calls with company stakeholders. Short calls with the operators you would publish alongside.
  3. Conversation with the founder. How you find a story in a dataset, where the honest denominator lives, and where you push back.
  4. Paid work trial (or Fast-Track Portfolio Review). Three days, paid, in our real environment: a first-party dataset, find the story, write the study. Fast-Track option: For exceptional candidates with verifiable published data studies and underlying methodology or SQL notebooks, we can fast-track through a live walkthrough of your published data work in place of a multi-day trial.

If the work above reads like yours but your resume is unconventional, apply anyway. We hire on the work and the reasoning, not the pedigree.

Compensation & Ownership

Total first-year compensation: $250,000 – $350,000 (base salary + target first-year ownership and profit-share).

  • Base salary: $160,000 – $210,000, top of market for this kind of role.
  • Target first-year ownership & profit-share: $90,000 – $140,000.

Product.ai is a profitable, founder-owned company generating ~$22M/yr in revenue with zero venture debt. Beyond base salary, operators participate in our Profit Interest Unit (PIU) ownership and profit-share program ($0 strike price units sharing in annual free-cash-flow distributions and tender liquidity, earned on performance milestones after joining, never day-one vesting). 100% company-paid family medical, dental, and vision premiums and an uncapped AI tooling budget steered by return.

Based in Santa Monica, Los Angeles, on our high-trust hybrid rhythm: four focused in-office half-days (Mon/Tue/Thu/Fri 9am–2pm), with Wednesdays and afternoons open to work from wherever you do your best work.