Thumbtack · Remote, Canada, CA · 7 days ago
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.
We’re looking for applied scientists with deep expertise in machine learning, optimization, building data products, and/or statistical models. As part of a small product team you will have full ownership over your domain, so you should be a person who dreams big, then executes well.
At Thumbtack, the Applied Science team is responsible for a wide variety of problems spanning AI, machine learning, statistics, and computer science:
As a Staff Applied Scientist on our New Hiring Experiences team, you will lead the technical direction for the matching and recommendation systems that connect millions of homeowners with the right service professionals. This is a staff IC role expected to influence and effectively partner with engineering and product leaders across retrieval, ranking, allocation, and pricing systems and teams: the core marketplace mechanics that determine whether the right customer finds the right pro at the right price.
You’ll help define the applied science technical roadmap for matching and recommendations, architect production ML systems that serve millions of daily matches, and partner with engineering, product, and economics leaders to evolve the marketplace. You’ll mentor senior applied scientists, raise the bar on technical rigor across the org, and be a voice on how agentic and LLM-powered experiences reshape what a marketplace can do for customers and pros.
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.
Note: Thumbtack uses AI tools to support our resume screening process. However, our Recruiting team’s expertise and judgment guide hiring decisions.
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.
Thumbtack embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, pregnancy, sexual orientation, gender identity or expression, religion, national origin, ancestry, citizenship, marital status, military or veteran status, genetic information, disability status, or any other characteristic protected by federal, provincial, state, or local law. We also will consider for employment qualified applicants with arrest and conviction records, consistent with applicable law.
Thumbtack is committed to working with and providing reasonable accommodation to individuals with disabilities. If you would like to request a reasonable accommodation for a medical condition or disability during any part of the application process, please contact: recruitingops@thumbtack.com.
If you are a California resident, please review information regarding your rights under California privacy laws contained in Thumbtack’s Privacy policy available at https://www.thumbtack.com/privacy/.
We put as much craftsmanship into candidate safety as we do into the hiring experience itself. While scammers may try to impersonate our team, we’ll never ask you for money, banking info, or SSNs during hiring. Check out our blueprint on how to spot the fakes. https://careers.thumbtack.com/recruiting-scams
Headquarters
Remote, Canada
Work Location
remote
Job Category
Data Science / AI / Machine Learning
Application Deadline
Not specified
Job Type
temporary
Experience Level
lead
Application Method
Apply via Website
Salary
232k - 300k CAD/year
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