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Applied Scientist, Customer Growth

CompraTica Empleos

EMP:Marketing
USA
Tiempo Completo
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Descripción

Thumbtack helps millions of people confidently care for their homes.

Thumbtack is the one app you need to take care of and improve your home — from personalized guidance to AI tools and a best-in-class hiring experience.

Every day in every county of the U.

, people turn to Thumbtack to complete urgent repairs, seasonal maintenance and bigger improvements.

We help homeowners know which projects to do, when to do them and who to hire from our growing community of 300,000 local service businesses.

If making an impact inspires you, join us.

Imagine what we’ll build together.

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the Applied Science Team The Customer Growth Applied Science team is responsible for delivering profitable growth to Thumbtack by developing and deploying state of the art Artificial Intelligence (AI) models in growth marketing and demand partnerships

Challenge At the core of our work lies vast amounts of user data.

We focus on delivering scalable experiences for a diverse, often unknown, user base by developing in-app features for onboarding, engagement, and reactivation, with constant experimentation.

Beyond traditional growth challenges like customer lifetime value, media strategy, and personalized user experiences, we are pioneering the use of generative AI models and agentic systems to empower marketers.

What you'll do Initiate and drive applied science initiatives to completion, with a focus on the business impact Build and deploy AI systems to production, examples: Customer Lifetime Value LLM-powered agentic systems to generate ad copies at scale and understand campaign performance across various segments Recommendation systems to drive user engagement Next best action models to personalize communications Analyze a wide variety of data: structured and unstructured, observational and experimental to drive model development Maintain the right balance between speed of execution and scientific rigor when designing solutions Own the reliability and performance of deployed models, includ.

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