Related skills
sql python scikit-learn pyspark xgboostπ Description
- Own product data quality across catalog and transactions, incl. matching and GPID
- Build production ML models for search, recommendations, and identity
- Create scalable data pipelines and monitoring for data quality
- Collaborate with Product teams to refine taxonomy and definitions
- Influence search relevance and reporting accuracy across the business
π― Requirements
- 5+ years in data science/ML/analytics; 2+ yrs in product data; degree preferred
- Production-grade data pipelines and model deployment
- Data quality expertise: completeness, accuracy, deduplication
- ML/classification for product data; search/retrieval pipelines
- Strong Python and SQL; ML libraries (scikit-learn, XGBoost, LightGBM)
- Embeddings, vector search, and related techniques
π Benefits
- Flexible working with responsible PTO
- Mental health and wellness: up to 12 therapy sessions per year
- RSUs with a 3-year vesting schedule
- Coursera subscription for ongoing learning
- Parental leave: 26 weeks primary caregiver; 13 weeks secondary
- Technology stipend and internet allowance
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