About the Role

We're hiring a Principal-level data leader to own and build J2's provider-data "recommendation engine" - the part of our product that recommends contracting leads to health insurers, and distills a single source-of-truth provider dataset out of noisy, conflicting, multi-source data.

This is a foundational role for the function. You'll set the vision for how J2 turns messy provider data into trustworthy, customer-facing data products; you'll be hands-on building it from day one; and you'll grow and lead the team behind it as it scales. The center of the job is judgment: looking at conflicting data and reasoning, fast and iteratively, toward an answer that makes sense to a real person.

There's significant room to expand the surface area from here, for example, validating a customer's own provider data against J2's source of truth and flagging the records most likely to be wrong.

This is a high-agency seat. We'll give you the problem and the leverage; you'll decide how to solve it and ship.
What you'll own

• The provider-data recommendation engine end to end, from the conceptual model of "what is true about this provider" through to the recommendations customers act on
• Distilling a source-of-truth provider dataset from many noisy, disagreeing sources, and being accountable for whether the output is right and useful, not just whether the pipeline runs
• Bringing LLMs to bear on ambiguous data-judgment problems, directing AI coding tools to do the building so you and your PM partner can spend your energy on the hard judgment calls
• Shipping iteratively and putting data products in front of customers, then sharpening them based on what actually drives value
• Building and leading the function over time, hiring behind you and scaling a team as the work grows

What success looks like

• First few months: you're hands-on-keys and shipping. You've built a working point of view on the source-of-truth model and put early recommendations in front of customers.
• Within the year: the recommendation engine is a real, trusted product surface; you've validated at least one adjacent expansion (e.g. customer-data validation); and you've begun building the team behind you.

About You

If the following capabilities describe you, you could be a strong fit for this role.
What you know

• A strong, opinionated point of view on how to apply LLMs to ambiguous data-judgment problems
• Deep familiarity with the realities of messy, multi-source data and what it takes to reconcile it into something trustworthy
• Enough business and product context to connect data work to customer value
• Knowledge and experience with our Tech stack is relevant but not gating, conceptual skills matter more than any particular stack. What we use today: strong Python, dbt, Postgres and LLM frameworks.

What you can do

• Look at conflicting data and reason quickly toward an output that makes sense to a human: speed, taste, and product sense are the qualities we're hiring for
• Productize your own work: turn a data judgment into a shipped, customer-facing product, not an internal dashboard or a research artifact
• Build hands-on today (strong Python; comfort across a modern data stack) while architecting for a team to scale behind you
• Direct AI coding tools effectively so the leverage shows up in how much you ship

What you're like

• Product-minded, not research-minded. You're energized by "how do I make sense of this messy data and ship something useful," not by abstract modeling for its own sake.
• Hungry and high-agency. This is the defining trait. You take an open-ended problem and run.
• Founder energy. You want to do the work now and build the function - both, not one.
• Commercially oriented. You instinctively ask whether the result actually makes sense and moves the customer, not just whether the job succeeded.

Experience & Background

• Senior / principal level, ~5-7 years is the sweet spot. We'd rather bet competitively on a high-caliber 5-7-year builder than insist on a longer track record.
• Real startup, 0-to-1 and 1-to-n product experience. You've built something from nothing and helped it grow.
• A track record of shipping data products that customers used, not internal BI or published research.

This might not be the right fit if...

• You think primarily in pipelines and infrastructure and measure success by whether the data moved, rather than by the quality and usefulness of the output
• You're drawn to abstract, research-oriented work and methodological rigor for its own sake. This is a fast, ambiguous, product-driven problem, and a heavily academic orientation tends to fight against it
• Your background is primarily statistical, actuarial, or finance-modeling and you're not genuinely excited by messy-data product judgment
• You want to manage rather than build. There's a team to grow here, but the leader has to love the hands-on work too
• You're looking for a lifestyle role. We protect work-life balance, but we want someone with real hunger.

Working Here

• New York City-based hybrid role (in-office 3x week). Remote work with quarter in-office visits possible for exceptionally qualified candidates.
• Competitive compensation, stock options, and health insurance.
• Unlimited PTO: take the time you need when you need it
• Commuter Benefits
• Stipend for at-home work machine and equipment
• A world-class team of fun, welcoming, ego-free, proven entrepreneurs with whom to build lifelong relationships

Compensation

The salary range for this role is $200K - 240K. Compensation will be determined based various factors, including but not limited to specialized skill sets, years of relevant experience, relevant certifications, and primary location.