Thumbtack needs to balance supply and demand in its marketplace, with a specific focus on acquiring, retaining, and enabling the success of larger, high-capacity, licensed professionals to meet high demand projections, unlock strategic partnerships, and enhance customer experience and platform growth.
Requirements
- Expert knowledge of machine learning techniques, including classification, anomaly detection, and natural language processing (NLP).
- 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
- 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
- Demonstrated ability to lead seamless execution.
Responsibilities
- Develop, deploy, and optimize machine learning models and algorithms for various supply shaping problems, including: Targeted large pro acquisition and lead scoring.
- Pro retention and churn prediction for high-value segments.
- Optimization of pro expansion (e.g., category, geo, budget).
- Enabling new features for marketplace matching and ranking algorithms specifically for large and licensed pros.
- Leveraging external data (e.g., credentialing databases) for pro quality assessment and targeting.
- Design and execute marketplace experiments to evaluate the effectiveness of new models, features, and strategies on key supply and business metrics.
- Analyze a wide variety of data, including marketplace interactions, pro profiles, financial data, and external data sources, to identify trends, opportunities, and risks related to supply health.
Other
- Initiate and drive applied science initiatives to completion with a focus on improving the acquisition, retention, and expansion of large professionals on the Thumbtack platform.
- 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 machine learning systems in production.
- Maintain the right balance between speed of execution and scientific rigor when designing solutions for a fast-paced marketplace environment.
- Contribute to improving the overall performance and robustness of supply shaping models by exploring new features, algorithms, and data sources.
- LI-Remote
