Senior Applied Scientist, Search & Booking
Thumbtack
- Toronto, ON
- Permanent
- Full-time
- Improve customer and service provider matching. Matching and optimization algorithms are fundamental to Thumbtack's product: we now service millions of matches per week. Identifying better matches between customers and service providers has an incredible impact on the experience of customers and professionals transacting on our platform.
- Model complex relationships in the presence of many confounding factors. Predictive modeling problems are everywhere across our product. Our team works to scope, design and implement machine learning models to support Thumbtack's product and marketing.
- Characterize marketplace dynamics. Thumbtack's marketplaces consist of thousands of active markets across our service categories and U.S. cities. Via exploratory data analysis and experimental design, our team works to understand trends and behaviors within these markets.
- Build a healthy marketplace. We evolve and manage the monetization mechanics of our marketplace, including defining the parameters that affect the prices we charge.
- Initiate and drive applied science initiatives to completion, with a focus on the business impact of those projects
- Architect and deploy machine learning systems and algorithms to production
- Design and execute experiments, collect and analyze data to characterize our product and marketing
- Analyze a wide variety of data: structured and unstructured, observational and experimental
- Collaborate with engineers, data scientists, and economists to use sound statistical practices
- Maintain the right balance between speed of execution and scientific rigor when designing solutions
- Technical mentorship of other applied scientists
- Expert knowledge of machine learning techniques, particularly as applied to search, ranking, and matching problems
- Experience with NLP techniques, including familiarity with modern LLM designs and tools
- 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
- Experience with technical mentorship of other applied scientists
- Demonstrated ability to create and drive technical and impactful roadmaps for the business, and lead seamless execution
- 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
- Expert knowledge of probability and statistics, including experimental design, predictive modeling, optimization, and causal inference
- Experience with large-scale distributed systems
- Ph.D. in a relevant field