Search & Recommendation Data Scientist(Intelligence Planning)
Tasks
- Analyze bias and regional differences and propose global algorithm rollout strategy
- Analyze user behavior logs for search recommendation problems
- Define offline online evaluation metrics and experiment design for A B testing
- Design statistical and machine learning models for personalization and ranking
- Develop features and domain variables for retrieval ranking recommendation and RAG LLM search
- Document model specifications feature requirements and evaluation protocols for implementation
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | B testing | CTR | CVR | Causal Impact | Causal Inference | Classification | Clustering | Embedding | LLM | MRR | Machine Learning | Multi-Armed Bandit | NDCG | Pandas | Python | R | RAG | Ranking | Recall | Recommendation Systems | Regression | Retention | Retrieval | SQL | Semantic Search | Spark | Statistics | Uplift Modeling
Education
Roles
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