Applied Scientist

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.S., 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.

About the Applied Science Team

We are creating new product initiatives to balance supply-demand needs across our marketplace by acquiring, retaining and enabling success for our larger professionals. Of particular focus will be high-capacity, licensed professionals with ambitions to grow with Thumbtack. We leverage machine learning, causal inference, and optimization to strategically acquire, retain, and expand pros. Our work directly contributes to meeting high demand projections, unlocking strategic partnerships, and ultimately enhancing customer experience and platform growth by ensuring a robust and high-quality supply base. We tackle a variety of complex problems at the intersection of marketplace dynamics, supply chain optimization, and behavior modeling.

The Challenge

Thumbtack constantly strives to balance supply and demand in our marketplace, focusing on adding supply with a high bar on quality. Our strategic focus now also includes larger pro partners. When left unconfronted, supply gaps can hinder strategic partnerships and revenue growth, acutely in high-demand markets. Our Pro Optimization and Pro Success teams design and implement data-driven strategies to proactively identify, attract, and nurture these critical supply segments. This involves overcoming challenges such as accurately forecasting supply needs, optimizing acquisition channels, ensuring seamless integration with external systems (e.g., FSMs/CRMs), and evolving marketplace mechanics (e.g., matching, ranking) to effectively serve large pros. We need to build sophisticated models that can understand and influence pro behavior, identify high-potential pros, and adapt to changing market dynamics to maintain a healthy and balanced marketplace.

What you'll do 

• Initiate and drive applied science initiatives to completion with a focus on improving the acquisition, retention, and expansion of large professionals on the Thumbtack platform.
• Develop, deploy, and optimize machine learning models and algorithms for various supply shaping problems, including:
• Targeted large pro acquisition and lead scoring.
• Pro retention and churn prediction for high-value segments.
• Optimization of pro expansion (e.g., category, geo, budget).
• Enabling new features for marketplace matching and ranking algorithms specifically for large and licensed pros.
• Leveraging external data (e.g., credentialing databases) for pro quality assessment and targeting.
• Design and execute marketplace experiments to evaluate the effectiveness of new models, features, and strategies on key supply and business metrics.
• Analyze a wide variety of data, including marketplace interactions, pro profiles, financial data, and external data sources, to identify trends, opportunities, and risks related to supply health.
• Collaborate closely with engineering, product management, business development, and marketing teams to define problems, develop end-to-end solutions, and ensure successful implementation and monitoring of machine learning systems in production.
• Maintain the right balance between speed of execution and scientific rigor when designing solutions for a fast-paced marketplace environment.
• Contribute to improving the overall performance and robustness of supply shaping models by exploring new features, algorithms, and data sources.

In order to be successful, you must bring

• Expert knowledge of machine learning techniques, including classification, anomaly detection, and natural language processing (NLP).
• Ability to effectively read, write, and debug code in programming languages such as Python
• Good knowledge of probability and statistics, including experimental design, optimization, and causal inference
• Ability to break down complex problems rigorously and understand the tradeoffs necessary to deliver impactful projects
• Ability to communicate clearly and effectively to cross functional partners of various technical levels
• Demonstrated ability to lead seamless execution.

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