onsite
Search & Recommendation Data Scientist - 42dot
Data Scientist
Data Scientist focused on global search and recommendation, leveraging user behavior, logs, and metadata to design ML models, ranking algorithms, and feature pipelines for personalized experiences and conversion optimization.
About the role
Key Responsibilities
- Analyze global user behavior, search logs, recommendation logs, and content metadata to define search/recommendation problems and improvement opportunities.
- Design statistical and ML model concepts for personalized recommendation, search ranking, user targeting, conversion prediction, and segment classification.
- Identify core features and domain variables for retrieval, ranking, recommendation, and LLM/RAG search, and define data requirements.
- Analyze regional user behavior differences, data bias, and business context to propose strategies for applying global search/recommendation algorithms.
- Validate new algorithm or model candidates through experimentation and performance evaluation.
Requirements
- Strong experience with Python, SQL, and machine learning libraries (scikit-learn, XGBoost, LightGBM, etc.).
- Proven track record in recommendation systems, ranking algorithms, and feature engineering.
- Knowledge of LLM/RAG search techniques and experience with large language models is a plus.
- Excellent analytical skills and ability to translate business problems into data-driven solutions.
- Fluent in English; Korean language skills are a bonus.
Skills
pythonmachine learningsqldata analysis