Data Scientist II, Marketing

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 how we set prices across hundreds of 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 that is committed to improving Thumbtack and improving each other.

About the Role

As a Marketing Data Scientist II at Thumbtack, you’ll be expected to leverage your analytical expertise, marketing knowledge, communication and collaboration skills to drive a variety of high-impact projects. You will embed directly with the paid marketing team to help optimize various marketing channels, drive personalization and discover new channels. Outside growth marketing work, you’ll contribute to our broader Data Science team and company data culture by sharing your learnings, partnering with others, and building new capabilities for how we can use data to guide decisions.

What you'll do

• Own end-to-end analytics for growth marketing, partnering with Marketing, Finance, and external partners to understand user behavior, define target audiences, measure campaign performance, and forecast and allocate budgets
• Translate ambiguous business questions into rigorous analyses and clear recommendations that improve individual campaign performance and optimize the overall marketing channel mix
• Design, execute, and interpret experiments and quasi-experiments to enable causal inference and inform high-stakes marketing investment decisions
• Partner closely with MarTech, Product Management, and Engineering to scope, build, and evaluate new capabilities—such as developing local market intelligence framework and improvements to customer LTV bidding systems—ensuring measurable performance gains
• Develop deep domain expertise in growth marketing measurement, experimentation, customer segmentation, and targeting optimization, and apply that expertise to influence strategy and execution
• Collaborate with cross-functional partners to build scalable analytical solutions, tools, and frameworks that unlock sustained growth
• Raise the bar for Thumbtack’s data culture by designing, maintaining, and documenting high-quality, trusted data tables and metrics that enable self-serve decision-making across teams

In order to be successful, you must bring

• Bachelor’s degree in statistics, mathematics, data science, economics, or a related quantitative field (advanced degree a plus)
• 3+ years of experience in marketing data science, strong understanding of digital marketing and experience with marketing measurement and performance optimization
• Advanced SQL skills, proficiency in Python or R, and experience using Looker or similar BI tools to drive insights
• Experience working with large and imperfect datasets at scale, and building and applying statistical and/or machine learning models to solve real-world business problems
• A passion for problem-solving and critical thinking, with the ability to navigate ambiguity and turn data into clear, actionable insights
• Strong business judgment and the ability to identify signal in noisy, imperfect data
• Excellent communicator and compelling storyteller, with the ability to listen deeply, explain complex concepts clearly, and influence cross-functional partners

Expected salary ranges

• For candidates living in San Francisco / Bay Area, San Jose, New York City, or Seattle metros, the expected salary range for the role is currently $164,900 - $213,400.
• For candidates living in Austin, TX or Washington DC metros or in California, Massachusetts, New Jersey, or Washington states, the expected salary range for the role is currently $148,800 - $192,500.
• For candidates living in all other US locations, the expected salary range for this role is currently $140,300 - $181,500.

Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role.