Sr. Data Scientist

Job Description:

Job Posted: July 21, 2025
Location: Americas (North, Central and South America), EMEA (Europe, the Middle East and Africa)

Zapier is hiring Senior Data Scientists to join our growing Data team and support two high-impact areas of the business: Enterprise (Upmarket), and Ecosystem. While each domain has its own focus, all roles share a common goal — 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.

As a Senior Data Scientist at Zapier, you won’t just analyze data, you’ll help build the systems and tools that turn insight into action. From designing lead scoring models and partner intelligence systems to tracking integration performance or delivering customer-facing usage analytics, your work will shape how we understand our users, optimize our operations, and scale our go-to-market strategies.

You’ll collaborate closely with cross-functional stakeholders in Product, Sales, Marketing, Success, and Finance, partnering with Data Warehouse Engineers to create scalable, reusable pipelines and analytical frameworks. In some cases, your work will feed into the product itself, helping Zapier users make smarter decisions, automate faster, and get more value from the platform.

Whether you're guiding how Zapier scales its enterprise motion, enriching our app ecosystem, or informing financial and GTM strategies, you’ll play a critical role in translating data into durable business leverage.

This is a high-impact opportunity for someone who blends technical excellence, product thinking, and a passion for building AI-informed, insight-driven systems that create lasting value at scale.

About You

• You’re technically fluent and hands-on. You bring senior-level experience—typically 5+ years—in data science or a related analytical role. You write production-grade Python (or R), write high-quality SQL, and design robust experiments and ML models that drive real-world impact. You’ve built systems that are as scalable as they are insightful.

• You think like a product builder. You design data products and models that don’t just explain what happened—they change what happens next. You thrive in ownership-heavy environments and approach problems like a PM: proactively ideating, prioritizing for impact, designing with users in mind, and iterating quickly.

• You’re fluent in AI and automation. You’re actively using modern AI tools (e.g. LLMs, AutoML, orchestration frameworks) to accelerate your workflows and solve new types of problems. You’re not just curious—you’re hands-on.

• You care deeply about quality and clarity. You hold a high bar for data instrumentation, statistical rigor, and communication. You simplify complexity, document thoroughly, and collaborate across technical and non-technical partners in a remote-first environment.

• You build for scale and enablement. You help teams define and own their KPIs, build self-serve dashboards, and use data to make better decisions faster. You create systems and documentation that make insight accessible—not just available.

• You value collaboration and knowledge sharing. You work effectively with teammates at all technical levels. You take ownership of filling knowledge gaps about the data products you manage and contribute to comprehensive documentation to elevate your peers with what you’ve learned.

Things 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 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; identifying business risks and opportunities through attribution data; understanding which customers benefit most from Upmarket offerings; and figuring out how to boost Upmarket’s contribution to revenue generation.

• Ensure all teams data-driven insights and can answer their own first-order questions. Develop data literacy programs and provide easy-to-use tools with clear documentation, examples, and tutorials.

• Perform basic ETL tasks to model new dimensions and facts in our data warehouse’s dimensional model. For the heavier lifts, you’ll be supported by Data Warehouse Engineering colleagues.

• Work with tools such as SQL, Looker, dbt, Databricks, Airflow, Eppo, and Python or R.