Squarespace's Domains Search team aims to solve the business problem of helping customers discover the perfect domain by leveraging advanced search, recommendation, and generative AI techniques. The goal is to create an intelligent platform that makes domain discovery intuitive and inspiring through natural language processing, ranking models, and personalization.
Requirements
- Foundation in machine learning and NLP, including practical experience with embeddings, transformers, or LLM applications.
- Proficiency in Python and SQL, with experience using data science and ML libraries (e.g., Pandas, Scikit-learn, PyTorch, TensorFlow).
- Experience with large-scale experimentation frameworks (A/B testing, causal inference, uplift modeling).
Responsibilities
- Design and evaluate algorithms for search, ranking, recommendation, and personalization of domain search results.
- Leverage NLP techniques (including LLMs) for query understanding, domain name generation, and contextual suggestions.
- Conduct rigorous experimentation and build metrics frameworks to measure search quality, engagement, and growth.
- Prototype and productionize models with MLEs, ensuring scalability, performance, and monitoring.
- Perform exploratory data analyses to identify opportunities, diagnose issues, and create product insights.
- Drive personalization strategies by incorporating user behavior, account history, and demographic data.
Other
- 5+ years of professional experience as a Data Scientist, with at least 2 in search, ranking, or recommender systems.
- Partner with engineers and product managers to translate ambiguous product needs into data-driven solutions.
- Mentor peers and help build a data science culture within the team.
- Hybrid role working from our New York City office 3 days per week.
- Report to the Senior Engineering Manager of Domains in NYC.
