Senior Data Scientist
Lead development of personalization and recommendation systems as an early data hire. Build ML pipelines, classification models, and data infrastructure from the ground up using SQL and Python.
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
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