Data Scientist

About Clerk

Clerk is on a mission to solve the user identity layer once and for all. We are a globally distributed team dedicated to providing best-in-class developer infrastructure to build the next generation of AI software. Today, we provide developers with full-stack React components and hooks like <SignUp/>, <SignIn/>, <UserProfile/>, useUser, and useOrganization. These APIs allow developers to build hard-to-get-right infrastructure for user identity, organization management and billing flows. We believe that a component is worth a thousand APIs.

What you will do

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.

Who you are

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.

• You have technical fluency. You know what rigorous data, ML and infrastructure work looks like, and you have high standards and strong opinions about it. Our stack (GCP/BQ, dbt, Dagster, ClickHouse, PostHog and Hex) will feel familiar or quick to learn.

Benefits

• Competitive Salary – We want you to know that we value the skills and experience you bring to the table. We go out of our way to make sure that you feel fairly compensated.

• Equity Ownership – At Clerk, we believe in shared success. That's why we offer a stock option plan so that everyone can benefit from the growth and prosperity of the company.

• Health Coverage – We care about your well-being. That's why we offer top-tier health insurance to ensure that your health needs are fully met.

• Work Gear – Set up your ideal home office with the gear of your choice. At Clerk, we want to ensure that you have everything you need to perform at your best.

• Flexible Vacation Policy – We believe in work-life balance and trust you to take the time you need. Although we recommend 25 days per year, our vacation policy is unlimited. This is in addition to observing national holidays specific to your country of residence.

• Diverse and Inclusive Team – Join our exceptional, diverse, and globally distributed team at Clerk. We are committed to fostering an inclusive environment where everyone can contribute their best in building impactful products and tools for the modern web.