Clerk Data Scientist at Clerk responsible for building machine learning infrastructure and product-facing data solutions. Owns ML pipelines from development to production and collaborates across engineering teams.
Responsibilities
You'll join a deliberately small and very senior data team to own machine learning and the product-facing side of Clerk's data. You'll take on ambiguous, greenfield problems and run them from the first question to production, in our repos and in engineering's.
We will expect you to:
Build Clerk's ML infrastructure. Stand up the pipelines, training and model serving that take ML from notebook to production, on what engineering already runs instead of a parallel stack.
Turn our own data into products. Start with the internal signals (conversion and expansion scoring, lifetime value, feature telemetry), then ship the useful ones to customers, including a semantic layer that gives them natural-language access to their own data.
Ship in engineering's repos, not just ours. Land models and signals in product and platform code with the teams that own it, and drive the cross-team work yourself.
Do whatever it takes for Clerk to succeed. Build a dashboard, dig into a trend, hop on a call with a customer. No task is beneath you and you care more about Clerk winning than about what's written in this job description.
Qualification
You're in the AmericasYou own largeYou work iteratively
Required
You're a Staff-level Data Scientist or ML Engineer who has built machine learning systems from scratch and run them in production, and you're just as comfortable building as analyzing. You love your craft. Experience in developer tools or infrastructure products is a plus.
You're in the Americas. You live in a location within ±3 hours of U.S. Mountain Time (MDT, UTC−06:00).
You own large, ambiguous problems. You're an individual contributor who wants a lot of scope and autonomy.
You cross the line between data and engineering. You're at home in the data stack, and just as comfortable opening a pull request in an adjacent engineering repo, learning how that team works, and getting it shipped. You have the product sense to know which problems are worth solving.
You work iteratively. Your process embodies a "ship and iterate" mentality, and you value the quick pace of a growing startup like Clerk.
Preferred
Experience in developer tools or infrastructure products
