Lead Data Scientist

ABOUT US:

Brisk Teaching is the leading AI platform for K-12 educators, empowering teachers to deliver personalized, curriculum-aligned instruction  Classroom Intelligence tools connect teachers, students, and curriculum—making meaningful learning happen in classrooms every day. We believe the best technology is cutting-edge, respects teachers’ time, integrates into real classrooms, and helps educators focus on what matters most.

Since launching, Brisk has experienced rapid growth. Over 2 million teachers use our platform, and we partner with districts and schools nationwide to transform how educators teach and how students learn.

We're backed by leading venture and edtech investors including Bessemer Venture Partners (Shopify, Linked In, Anthropic, Perplexity) and Owl Ventures (Newsela, Quizlet, Master Class), with a team spanning top AI companies and real classroom experience.

We're a fast-moving, collaborative team driven by a shared commitment to educator impact and product excellence. Our values—urgency, ownership, and focus—shape how we build and who we are.

We've already started building something we think fundamentally rethinks how data science gets done at a company. We have an internal data agent that can query our warehouse, interpret results, and surface insights to stakeholders directly. It works. People use it. And it's changed how our team operates day to day.

Now we need someone to take it further. As Brisk's product and organization grow, the systems underneath need to grow with them: a more robust semantic layer, better tooling for experimentation, more sophisticated automation across the data lifecycle, and the strategic thinking to decide where AI amplifies the team's work and where it replaces manual processes entirely.

This role is equal parts strategy and execution. You'll own the vision for how data drives decisions across Brisk, scale the AI-native workflows we've started, and build the systems that turn a small data team into one that operates like a much larger org. You'll report directly to leadership and have a seat at the table on product strategy, go-to-market, and company priorities.

• Set the data strategy: Define what we measure, how we measure it, and what "good" looks like. Establish the metrics architecture that connects product usage, retention, monetization, and growth into a coherent picture, and make sure every team at Brisk is oriented around it.

• Turn the data team into a product team: Build internal data products that stakeholders across the company actually use daily. Replace ad-hoc requests with self-serve AI interfaces, automated reports, and tools that make data accessible to non-technical teammates.

• Make the warehouse AI-readable: Build the semantic layer, documentation, and context infrastructure that lets both humans and AI systems query Brisk's data accurately. A well-documented warehouse is the foundation for every AI-powered workflow that follows.

• Build AI into the data lifecycle: Identify where AI agents, automated pipelines, and LLM-powered tooling can replace manual work: dbt model generation, data quality monitoring, experiment analysis, insight delivery. Ship these systems into production.

• Own product analytics and experimentation: Partner with Product, Engineering, and Design to design experiments, interpret results, and deliver the insights that shape what we build. Bring rigor to how we evaluate features and make ship/no-ship decisions.

• Drive growth and business intelligence: Maintain and evolve dashboards and reporting for Sales, Marketing, Customer Success, and leadership. Ensure the metrics that matter are visible, trusted, and actionable.

• Scale through systems, not headcount: Build infrastructure and…