Applied Scientist (Pro Growth)

Join Thumbtack, a platform dedicated to helping small business owners thrive. As an Applied Scientist on the Pro Growth team, you will have full ownership of your domain and work on a variety of problems spanning AI, machine learning, statistics, and computer science. Your work will directly contribute to meeting demand projections, unlocking strategic partnerships, and enhancing customer experience. You will 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 ML systems in production.

• Ownership of the domain, from problem framing to deploying models to production.
• Building models and experiments that shape pro acquisition, activation, and retention.
• Collaborating with cross-functional teams to define problems and develop end-to-end solutions.
• We’re looking for applied scientists with deep expertise in machine learning, optimization, building data products, and/or statistical models
• Familiarity with modern LLMs (OpenAI, Anthropic Claude, Gemini, AWS Bedrock) and experience with agentic AI development practices and tools
• Ability to communicate clearly and effectively to cross-functional partners of various technical levels
• 3+ years of industry experience as an applied scientist, data scientist, or ML engineer with ownership of production ML models
• Master’s degree in a quantitative field (Computer Science, Machine Learning, Statistics, Operations Research, Economics, or related), or equivalent industry experience
• Experience in applied science within a marketplace, supply chain, or growth domain
• Good knowledge of probability, statistics, and econometric methods, including experimental design, causal inference, and optimization
• Ability to effectively read, write, and debug code in programming languages such as Python and SQL
• Demonstrated ability to drive seamless execution end-to-end on at least one production ML project
• Experience with large-scale distributed systems (Spark, Databricks, or similar)
• Solid knowledge of machine learning techniques such as classification, regression, embedding-based approaches, and causal inference
• Ability to break down complex problems rigorously and understand the tradeoffs necessary to deliver impactful projects