Senior Data Scientist, Product Data
Tasks
- Assess GPID coverage and accuracy
- Build dashboards and recurring KPI reports
- Build data quality monitoring dashboards
- Build deduplication and entity resolution pipelines
- Build matching algorithms for transactions to products
- Build product graph infrastructure
- Build product search and retrieval pipelines
- Build scalable data pipelines
- Conduct catalog data quality analysis
- Define and track data quality KPIs
- Deploy ML models to production
- Detect duplicates and product variants
- Develop product classification and taxonomy models
- Ensure ML monitoring and reliability in production
- Evaluate search relevance and ranking quality
- Implement vector search and semantic similarity
- Improve classification accuracy
- Measure sales transaction match rates
- Monitor production model performance
- Set up alerting and anomaly detection
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Anomaly Detection | B testing | CI/CD | Clustering | Cosine similarity | Data Pipelines | Data Quality | Data profiling | Embeddings | Entity Resolution | Faiss | Fuzzy Matching | Levenshtein distance | LightGBM | Machine Learning | Model Monitoring | Nearest neighbor | Nearest-Neighbor Search | Pandas | Pinecone | PySpark | PyTorch | Python | Ranking | SQL | Scikit-learn | Semantic similarity | TensorFlow | Vector Search | Weaviate | XGBoost
Education
N/A
Roles
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