Senior Product Manager, Pricing

AI-native. You use AI daily - scenario modeling, pricing analysis, data exploration, drafting specs. You push AI into parts of your workflow others haven't thought of yet.

This is unlikely to be a good fit if you view AI as a novelty rather than a core productivity lever.

A systems thinker who architects platforms, not just sets prices. You see pricing as a system: inputs, rules, feedback loops, edge cases. You can design a pricing architecture that handles 24 services across 3 brands with different economics - and explain it to an engineer in a way they can build.

This is unlikely to be a good fit if your pricing experience is limited to spreadsheets or optimizing a single product's price point.

Data-informed, not data-dependent. You partner with the data team to define what to optimize and interpret results. You know when the data is insufficient and a judgment call is needed.

This is unlikely to be a good fit if you either ignore data or refuse to move without perfect information.

Technically fluent. You work directly with engineers on API design, discuss schema tradeoffs, and review technical design docs with real feedback. You don't write code, but you earn engineering's trust by speaking their language.

This is unlikely to be a good fit if you treat engineering as a black box or need everything translated into business terms.

A patient builder. The pricing gains require infrastructure first - a pricing API, a data product, migration tooling. You're energized by building the foundation, not frustrated that the payoff isn't immediate.

This is unlikely to be a good fit if you need quick wins to stay motivated or lose interest when the work is foundational.

Monetization-minded. You see bundles, add-ons, service availability, and frequency pricing as revenue levers, not just features. You naturally think about margin, willingness to pay, and Pro economics.

This is unlikely to be a good fit if you think of pricing as a one-time decision rather than an ongoing optimization problem.

- A quick-wins role. Massive technical debt (1.8M-row pricing tables, hardcoded logic across APIs). The pricing API and data product must be built before dynamic pricing gains materialize.

If you need visible impact in 90 days, this will be frustrating. - A solo act. Every pricing change touches engineering, data, sales, and support. If you prefer autonomous execution with minimal coordination, the dependency load here will feel heavy. - A data science role.

You partner closely with the data team, but you're not building pricing models. If you want to spend your days in notebooks running regressions, this isn't the right fit. - An optimization-only role. You're building a pricing system from scratch while keeping the current ones running.

If you prefer optimizing within an established framework, the ambiguity here will be uncomfortable.

- Base salary : $140,000 - $185,000 - Equity : Pricing decisions directly impact revenue, margin, and conversion at scale. We want you invested in the long-term outcome of the system you're building. - Healthcare : Medical, dental, and vision - Fully remote : Pricing work requires deep analysis and focused thinking. We trust you to manage your environment. - Flexible PTO : We focus on results.

Take what you need.

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