Zapier is hiring a Staff Data Scientist to join our Data team and support high-impact areas of the business, primarily focused on growing our platform. Your mission is to design and deliver data products and insights that accelerate decision-making, power intelligent features, and enable both internal teams and customers to move faster with confidence.

What You'll Do

Build and deploy data products that serve both internal and external customers.
Develop scalable frameworks for efficiently deploying models and deriving actionable insights.
Analyze user behavior to identify and explain key drivers of outcomes such as discovery, activation, engagement, upgrades, and churn.
Collaborate with business teams to design, analyze, and interpret experiments aimed at improving key metrics.
Conduct proactive research into high-potential areas, including defining data-driven customer segments and success signals to dynamically shape the product experience.
Perform ETL tasks to model new dimensions and facts in our data warehouse’s dimensional model.
Ensure all teams have data-driven insights and can answer their own first-order questions through data literacy programs, easy-to-use tools, and clear documentation.
Elevate other data teammates and the data org with clear documentation, demos, tutorials, best practices, automated tooling, and hands-on mentorship.

What We're Looking For

7+ years in data science or a related analytical role.
Experience writing production-grade Python or R and high-quality SQL.
A track record of designing robust experiments and ML models that drive real-world impact.
Proven ability to turn data into strategic insight and build scalable, insightful systems.
Business-minded with confidence in stakeholder management and working with senior leaders.
A product builder mindset, designing data products and models that change outcomes.
Fluency in AI and automation, actively using modern AI tools like LLMs, AutoML, and orchestration frameworks.
A focus on quality and clarity, holding a high bar for data instrumentation, statistical rigor, and communication.
An enablement approach, helping teams define KPIs, build self-serve dashboards, and use data to make better decisions.
Strong written communication skills and a value for collaboration, continuous learning, and knowledge sharing.

Technical Stack

SQL, dbt, Databricks, Looker, Airflow, Eppo, Python, R

Team & Environment

You will collaborate closely with cross-functional stakeholders in Product, Marketing, and Engineering, partnering with Data Warehouse Engineers and AI/ML Engineers.