Senior Data Scientist

Responsibilities

• Design and prepare high-quality data for personalization models: own data cleaning, feature selection, and model selection to build high-performing personalization models
• Build and maintain scalable pipelines for modeling data: develop robust ETL/ELT pipelines transforming raw behavioral, transactional, and catalog data into features using SQL and Python
• Optimize infrastructure to support ML personalization at scale: enhance data architecture and processing frameworks for real-time and batch modeling needs
• Ensure strong data governance and documentation: implement best practices for data quality, observability, and lineage across model-bound datasets
• Collaborate with Product and Engineering on instrumentation and feature tracking: ensure accurate tracking of user actions and translate business needs into modeling requirements
• Optimize classification models: develop and refine classification models that categorize events through feature engineering, tuning, and iteration

Requirements

• 5+ years of hands-on experience in data science or analytics engineering
• Expert proficiency in SQL and Python for data cleaning, feature engineering, and building production-ready modeling pipelines
• Strong ability to design experiments, evaluate model performance, and communicate insights to technical and non-technical stakeholders
• Experience building personalization and recommendation systems (ranking, classification, or personalized UX models) in production
• Experience working with cloud data platforms, analytics tooling, and best practices in data modeling and ML optimization
• Background building the early foundation of a data team at a small tech company/startup

Nice-to-Haves

• Experience with AWS Personalize, SageMaker, or similar cloud ML platforms
• Experience working on consumer-facing products at scale