Senior Data Scientist, Product

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 that is committed to improving Thumbtack and improving each other.

About the Role

Data Scientists at Thumbtack are empowered early on to leverage their critical thinking, interpersonal, and technical skills to make a positive impact on the company. Data Scientist embed with product teams to support new product feature launches, study the economics of our massive and dynamic marketplace, and help inform strategy. As a Data Scientist, you’ll be the person responsible for all the analytical needs of an entire team of engineers, designers, and product/marketing managers -- helping empower the team and Thumbtack more broadly to build the best product, as quickly as possible.

 Responsibilities

• Propose and conduct quantitative research into key user behaviors, product flows, and business trends; based on analysis and in collaboration with cross-functional partners, identify potential new opportunities and next steps for the product team
• Design and analyze experiments and other tests for causal inference, in collaboration with engineers, applied scientist, and economists
• Partner with product managers, engineers, etc. to help scope new features, e.g., scenario modeling for possible impact on key metrics, make recommendations on business logic of new features, etc.
• Define and monitor key metrics; investigate changes in metrics and propose next steps
• Develop topic area expertise, e.g., develop a deep understanding of how Thumbtack search works and interacts with other systems
• Contribute to our team and company data culture through accessible data table design and maintenance
• Collaborate with, mentor, and help recruit team members

What you’ll need

If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.

• 5+ years of experience in data science, analytics or economics
• Experience managing stakeholders with competing priorities in areas such as Product Management, Design, Engineering and Marketing
• Experience scoping, analyzing, and communicating results of experiments
• Expert in SQL 
• Strong communication skills and ability to build strong relationships cross-functionally and with leadership
• Bachelor’s, Master’s, or Doctoral degree in a technical area such as: Statistics, Engineering, Analytics, Math, Computer Science, Operations Research, Economics

Bonus points if you have

• A well-balanced combination of big-picture thinking, ability to thrive in ambiguity, exceptional problem solving skills and patience to teach others and uphold a high bar
• Experience working on a 2-sided marketplace 
• Proficient in one of Python or R
• Data visualization and segmentation skills in tools like Tableau or Looker
• Comfortable with code repository and version control tools like Git

Thumbtack is a virtual-first company, meaning you can live and work from any one of our approved locations across the United States, Canada or the Philippines.* Learn more about our virtual-first working model here.

For candidates living in San Francisco / Bay Area, New York City, or Seattle metros, the expected salary range for the role is currently $140,250 - $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.

For candidates living in all other US locations, the expected salary range for this role is currently $119,212.50 - $154,275. 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.

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