Senior Data Scientist, Lifecycle

About the Data Science Team

The Data Science team empowers Thumbtack to use data to guide business decisions. We collaborate with partners across the company to solve the most analytically challenging problems — everything from informing how we set prices across almost a thousand local services categories, to evaluating the impact of a new business model on company performance, to identifying early predictors of high-quality customers. We are a tight-knit, intellectually curious team committed to improving Thumbtack and improving each other.

About the role

As a data scientist on the experience led growth team, you will partner with a world-class cross-functional team — lifecycle marketers, product managers, engineers, and applied scientists— to build the analytical foundation that powers Thumbtack’s full lifecycle strategy for both homeowners and pros. This is a high-ownership role at the intersection of measurement, product analytics and applied science, where you will shape how Thumbtack thinks about engagement across the entire customer and pro journey.

You will be embedded in the Lifecycle Center of Excellence (COE), which is expanding its mandate from homeowner lifecycle to include pro lifecycle. The team’s priorities span personalized contextual communications, in-app lifecycle experiences, and the foundational data infrastructure and tooling needed to deliver these at scale — including end-to-end funnel reporting, self-serve analytics tooling, and measurement frameworks that cover the full lifecycle.

You will use your technical leadership to identify opportunities across both homeowner and pro lifecycle, develop a unified view of engagement on the Thumbtack platform, and partner with data engineering to build the data infrastructure that enables the team to move faster. You will be leading long-term initiatives with significant ambiguity, exercising independent judgment, and influencing senior cross-functional partners with the implications of your work.

What you’ll do

• Build the Lifecycle measurement framework — define lifecycle health metrics for both homeowner and pro, design experiments with appropriate rigor, and navigate attribution and contamination challenges in ambiguous measurement contexts.
• Build relationships with cross-functional teams across pro and homeowner lifecycle. Understand strategic challenges and contextualize them to use data to unlock new growth levers and inform product roadmap.
• Synthesize evidence across data sources to produce insights that shift senior leaders’ mental models — going beyond what happened to explain why and what to do next across the full pro and customer lifecycle; provide analytical rigor for the evolution toward intelligent, customer-centric decisioning and personalization.
• Serve as the tech lead for the Lifecycle — influence senior cross-functional partners, drive pillar-level alignment through insights and partnership. Be opinionated about strategic decisions and trade-offs based on your deep domain knowledge.
• Continue to evolve workflow automation and self-serve. Discovering new ideas, implementing POCs and coaching fellow DS team members.

In order to be successful, you must bring

• Bachelor’s or Master’s degree in Statistics, Math, Economics, Computer Science, or another STEM field.
• 5+ years of experience in a highly analytical role, with strong proficiency in SQL and Python for working with large, complex datasets.
• Cultivated a reputation as a trusted advisor to senior leadership and diverse cross-functional teams esp. managing non-technical stakeholders, leveraging insights to build consensus and influence strategy across product, marketing, and engineering, successfully influencing without direct authority.
• Proven track record of independently leading long-term, ambiguous analytical initiatives with measurable business impact — not just executing defined analyses but scoping and shaping the work.
• Deep expertise in experimental design, causal inference, and statistical methods — with the ability to navigate ambiguity in measurement contexts and communicate uncertainty clearly to non-technical stakeholders.
• Experience building data products — dashboards, self-service tools, or reusable analytical frameworks — that scale beyond your immediate team.
• Strong business acumen and ability to connect data findings to lifecycle strategy, making crisp prioritization recommendations under uncertainty.

Expected salary ranges

• For candidates living in Ontario and British Columbia, the expected salary range for the role is currently $160,700.00 - $207,900.00.